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id: cord-350373-dftdxzsm
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   key: cord-350373-dftdxzsm authors: Rayman, G.; Lumb, A.N.; Kennon, B.; Cottrell, C.; Nagi, D.; Page, E.; Voigt, D.; Courtney, H.C.; Atkins, H.; Platts, J.; Higgins, K.; Dhatariya, K.; Patel, M.; Narendran, P.; Kar, P.; Newland‐Jones, P.; Stewart, R.; Burr, O.; Thomas, S. title: Dexamethasone therapy in COVID‐19 patients: implications and guidance for the management of blood glucose in people with and without diabetes date: 2020-08-02 journal: Diabet Med DOI: 10.1111/dme.14378 sha: doc_id: 350373 cord_uid: dftdxzsm The RECOVERY (Randomised Evaluation of COVid‐19 thERapY) trial found that dexamethasone 6 mg once per day for 10 days reduced deaths by one‐third in ventilated patients and by one‐fifth in other patients, receiving oxygen therapy. This equates to the prevention of one death in around eight ventilated patients, or one in around 25 patients requiring oxygen. This article is protected by copyright. All rights reserved The RECOVERY (Randomised Evaluation of COVid-19 thERapY) trial found that dexamethasone 6 mg once per day for 10 days reduced deaths by one-third in ventilated patients and by one-fifth in other patients, receiving oxygen therapy [1] . This equates to the prevention of one death in around eight ventilated patients, or one in around 25 patients requiring oxygen. This welcome news has been considered such an important therapeutic advance that the regimen has been fast-tracked in the UK even though the study has yet to attain peer review publication. Although described by the investigators as 'low dose dexamethasone therapy' the dose is in effect five-to six6 fold greater than the therapeutic glucocorticoid replacement dose. High doses of glucocorticoids exacerbate hyperglycaemia in people with diabetes, may unmask undiagnosed diabetes and, in those at risk of diabetes, may precipitate hyperglycaemia and new-onset diabetes (commonly termed 'steroid-induced diabetes'). Furthermore, glucocorticoids are the commonest cause of people with diabetes developing potentially life-threating hyperglycaemic hyperosmolar state (HHS) in hospital. To prevent these harms, the Joint British Diabetes Societies (JBDS) published guidelines on the management of inpatients with and without diabetes receiving steroid therapy [2] . However, these guidelines, which have been adopted in most UK hospitals, may not be appropriate for those with severe COVID-19 infection receiving dexamethasone, given the additional impact of the disease on glucose metabolism. The 'cytokine storm' resulting from severe COVID-19 infection is associated with significant insulin resistance and reduced insulin production from the pancreatic  cells. This dual pathology can precipitate severe hyperglycaemia, life-threatening ketoacidosis and HHS in people with diabetes, and even in people without, diabetes [3] . To prevent these harms, the UK National Diabetes COVID-19 response group published in this journal guidance on the management of COVID-19-related hyperglycaemia [4]. However, given the 'triple insult' of dexamethasone-induced impaired glucose metabolism, COVID-19-induced insulin resistance and COVID-19 impaired insulin production, we now provide new guidance specifically for use in people with severe COVID-19 infection commencing dexamethasone. The aim is to ensure that all patients commenced on dexamethasone, whether or not they have diabetes, receive appropriate glucose surveillance and management of hyperglycaemia should it occur. The guidance informs the clinician of the key facts pertaining to this clinical situation and the reasons why these recommendations differ from the JBDS guidelines. It describes the frequency at which capillary blood glucose monitoring should be This article is protected by copyright. All rights reserved undertaken in those with and without diabetes and gives the target ranges of capillary blood glucose levels to aim for. The guidance recommends giving correction doses of rapid-acting analogue insulin when capillary blood glucose > 12.0 mmol/l, with the dose calculated according to the patient's weight or in those already treated with insulin, on their total daily insulin dose. The correction doses recommended are notably higher than those used in our previous hyperglycaemia guideline given the inevitable increase in insulin resistance. Unlike the previous guidance, we do not recommend using the insulin correction ratios that some people with type 1 diabetes usually use as these may not be appropriate given the significant disturbance of glucose metabolism. To maintain glycaemic control we recommend using NPH insulin which has an intermediate duration of action in preference to longer-acting insulin even though the metabolic effects of dexamethasone can persist for up to 36 h. NPH insulin given twice daily allows more flexibility in dose adjustment. The starting doses based on weight are slightly greater than those given in our previous guidance but as before, a reduced dose should be used in the frail, elderly and those with an eGFR of < 30 ml/min. If the patient is already on a long-acting insulin or twice daily pre-mix insulin then it is recommended this be increased by 20%, but it is noted that this may actually require rapid escalation by 40% or more [5] . Insulin resistance will fall when dexamethasone is stopped and so capillary blood glucose and insulin dose adjustment need careful monitoring to avoid hypoglycaemia. The guidance table for the NPH and long-acting insulin assists in dose escalation and down titration of these insulins. Finally, close initial follow-up is advised for those with known diabetes and a yearly HbA 1c measurement is recommended for those with steroid-induced hyperglycaemia because this group have been shown to be at increased risk of developing diabetes at a later date. We hope that these guidelines will be helpful for those managing patients with COVID-19 treated with dexamethasone in the ward setting. Although not intended for critical care units where policies around blood glucose monitoring may differ and where insulin is likely to be given by intravenous infusion, the guidelines may be adapted for use in this setting. COncise adVice on Inpatient Diabetes (COVID:Diabetes): › Dexamethasone reduces mortality in people with COVID-19 who require ventilation or oxygen therapy › Corticosteroid therapy impairs glucose metabolism and is the commonest cause of life threatening inpatient Hyperglycaemic Hyperosmolar Syndrome (HHS) › COVID-19 increases insulin resistance and impairs insulin production from the pancreatic beta cells; this can precipitate hyperglycaemia and life threating Diabetic Ketoacidosis (DKA) in people with diabetes and even in people not known to have diabetes › Glucose levels above 10.0 mmol/L have been linked to increased mortality in people with COVID-19 › The recommended dexamethasone dose of 6mg/day (oral or IV) for 10 days, equivalent to 40mg of prednisolone/day, will undoubtedly afect glucose metabolism › Thus, the triple whammy of dexamethasone induced impaired glucose metabolism, COVID-19 induced insulin resistance and COVID-19 related impaired insulin production could result in signiicant hyperglycaemia, HHS and DKA in people with and without diabetes, increasing both morbidity and mortality › Sulphonylureas are NOT recommended in this context as beta cell function may be impaired and insulin resistance is likely to be severe. For this reason, these recommendations difer from those in the JBDS guideline on the Management of Hyperglycaemia and Steroid (Glucocorticoid) Therapy q To ensure ALL patients on dexamethasone receive appropriate glucose surveillance and appropriate management of hyperglycaemia Target glucose 6.0 -10.0 mmol/L (up to 12.0 mmol/L is acceptable) Check the glucose at least 6 hourly ideally at fasting periods (e.g. before meals and at bedtime). If after 48 hours all fasting glucose results are <10.0 mmol/L reduce frequency to once daily at 17.00-18.00 hrs. Continue until dexamethasone is stopped If any fasting glucose is above 10.0 mmol/L continue 6 hourly monitoring and follow the guidance below to correct hyperglycaemia i.e. glucose above 12.0 mmol/L Throughout the admission, check fasting glucose at least 6 hourly, or more frequently if the glucose is outside the 6.0 -10.0 mmol/L range q This guidance is for use in ALL patients with COVID-19 who are treated with dexamethasone in a ward setting Use subcutaneous rapid acting insulin analogue (Novorapid®/Humalog®/Apridra®) as described below. Note these are conservative doses and depending on response in individual patients, as previously stated, may need to be increased rapidly (or where more insulin sensitive, decreased) Recheck glucose at 4 hrs to determine response and whether a further correction dose is needed Follow the weight-based tables below in those people: » not known to have diabetes » with type 2 diabetes treated with diet alone or with oral hypoglycaemic agents Where the total daily dose (TDD) of insulin is known follow the guidance in the Increase the long acting basal or NPH insulin by 20% but this may need rapid escalation by as much as 40% depending on response. Titrate the dose using the tables below. Patients on basal-bolus regimens may not require 'mealtime' insulin boluses if not eating, however, if hyperglycaemia persists during adjustment of basal insulin then use corrective rapid acting insulin doses according to total daily insulin dose (TDD) or weight given in the table for correction doses of rapid acting insulin Leicester Diabetes Centre › People on twice-daily pre-mix insulin e.g. NovoMix 30®/Humulin M3®/Humalog Mix 25®/Humalog Mix 50® Consider increasing the morning dose by 20% but this may need rapid escalation by as much as 40% each day depending on the response Doses can be titrated daily, although longer-acting insulins may take 48-72 hours to reach steady state. Dose adjustments will afect blood glucose throughout the day If the person is too unwell to manage their pump, transfer to a Variable Rate Intravenous Insulin Infusion (VRIII) with a basal insulin given alongside -seek the advice of the diabetes team. If the pump is removed, give the pump to a relative for safekeeping or label with the patients details and safely store Those people well enough to manage their subcutaneous insulin infusion pump should be recommended to initially increase the basal rates by 20% and be made aware that this may need to be increased further on a daily basis. Refer all people using a personal insulin pump to the diabetes team Insulin resistance will begin to fall when the dexamethasone has been stopped but may take a number of days. Continue to monitor glucose 6 hourly and down titrate using the guidance table above Normoglycaemia may be established after stopping dexamethasone without the need for ongoing diabetes therapy. However, up to a third of people may later develop diabetes therefore alert the GP that the patient will need a yearly HbA1c measurement › People with known diabetesThese patients will require close support following discharge. The discharge guidelines and patient information lealet produced by this group are available to facilitate this. The lealet can be accessed here: https://www.diabetes.org.uk/professionals/resources/shared-practice/inpatient-and-hospital-care#patients 


id: cord-026990-d3l1sbeb
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   key: cord-026990-d3l1sbeb authors: Oberoi, Sumit; Kansra, Pooja title: Economic menace of diabetes in India: a systematic review date: 2020-06-17 journal: Int J Diabetes Dev Ctries DOI: 10.1007/s13410-020-00838-z sha: doc_id: 26990 cord_uid: d3l1sbeb AIM: Diabetes mellitus is recognised as a major chronic pandemic disease that does not consider any ethnic and monetary background. There is a dearth of literature on the cost of diabetes in the Indian context. Therefore, the present study aims to capture the evidence from the literature on the cost of diabetes mellitus in India. METHODS: An extensive literature was reviewed from ACADEMIA, NCBI, PubMed, ProQuest, EBSCO, Springer, JSTOR, Scopus and Google Scholar. The eligibility criterion is based on ‘PICOS’ procedure, and only those studies which are available in the English language, published between 1999 and February 2019, indexed in ABDC, EBSCO, ProQuest, Scopus and peer-reviewed journals are included. RESULTS: A total of thirty-two studies were included in the present study. The result indicates that the median direct cost of diabetes was estimated to be ₹18,890/- p.a. for the north zone, ₹10,585/- p.a. for the south zone, ₹45,792/- p.a. for the north-east zone and ₹8822/- p.a. for the west zone. Similarly, the median indirect cost of diabetes was ₹18,146/- p.a. for the north zone, ₹1198/- p.a. for the south zone, ₹18,707/- p.a. for the north-east and ₹3949/- p.a. for the west zone. CONCLUSION: The present study highlighted that diabetes poses a high economic burden on individuals/households. The study directed the need to arrange awareness campaign regarding diabetes and associated risk factors in order to minimise the burden of diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13410-020-00838-z) contains supplementary material, which is available to authorized users. 'Diabetes is a metabolic disease characterised by hyperglycemia resulting from defects in insulin secretion, insulin action or both' [1] . With rising pervasiveness globally, diabetes is conceded as a major chronic pandemic disease which does not consider any ethnic background and monetary levels both in developing and developed economies and has also been designated with the status of 'public health priority' in the majority of the countries [2, 3] . Individuals with diabetes are more susceptible to develop any of the associated complications, viz. macrovascular or microvascular. As a consequence, people experience frequent and exhaustive confrontation with the health care systems [4] . The treatment cost for diabetes and its associated complications exert an enormous economic burden both at the household and national levels [5] [6] [7] [8] [9] . In a developing nation like India, the majority of diabetes patients experience a substantial cost burden from out-ofpocket (OOP). Also, the dearth of insurance schemes and policies escalate the cost of diabetes care [2] . Instantaneous urbanisation and socio-economic transitions, viz. rural to urban migration, low exercise regimen, lifestyle disorder, etc., have resulted in an escalation of diabetes prevalence in India over the last couple of decades [10] [11] [12] [13] [14] . According to the International Diabetes Federation [15] , 'India is the epicentre of diabetes mellitus and it was found that in 2017 India had the second-largest populace of 73 million diabetic patients, after China. And the figure is expected to be just double 134 million by 2045'. Considering that fact, the epidemiologic transition of diabetes has a colossal economic burden [16] . The estimated country-level health care expenditure on diabetes mellitus in India after amending purchasing power difference was 31 billion US dollars in 2017, pushing India in fourth place globally after the USA, China and Germany. Looking at the economic burden, in India, diabetes alone exhausts 5 to 25% share of an average Indian household earning [17] [18] [19] . Chronic nature and the rising epidemic of diabetes have everlasting consequences on the nation's economy and health status [20] . Therefore, managing diabetes and its comorbidities is a massive challenge in India due to several issues and stumbling blocks, viz. dearth of awareness regarding diabetes, its risk factors, prevention strategies, health care systems, poverty-stricken economy, non-adherence to medicines, etc. Altogether, these issues and problems remarkably contribute to the economic menace of diabetes in India [20] [21] [22] [23] [24] . After a perspicuous representation of the economic menace of diabetes in India, policymakers and health experts should provide healthier prospects to enhance the quality of life of millions [19] . Thus, the present study aims at capturing the evidence from the literature on the cost of diabetes mellitus in India, reviewing the materials and methods used to estimate the costs and, lastly, exploring future research area. For the accomplishment of the objective, the paper has been divided into five sections. The 'Introduction' section of the study discusses diabetes and its economic burden. The 'Materials and methods' section deals with materials and methods applied for data extraction and quality assessment. The 'Results' section of the present study reports the results of the study. The 'Discussion' section concludes the discussion along with policy implications and limitations. A comprehensive literature review was carried out by following the 'Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines' [25] . The article suggests a minimum set of guidelines and procedures of writing items to enhance the quality of the systematic review. A search was performed between February and March 2019 for the accumulation and review of studies published up to January 2019. [25] . Later, 187 articles were identified to be duplicate and removed immediately. Of the total 225 articles, limited studies managed to clear the eligibility criterion based upon the significant elements of the 'Patient Intervention Comparison Outcome Study (PICOS)' procedure [26] . Title, abstract and keywords of the remaining 225 studies were assessed to determine their relevance. Those articles which have been included (a) were available in English language; (b) were published between 1999 and February 2019; (c) were indexed under ABDC, EBSCO, ProQuest and Scopus; (d) were under journals that are to be peer-reviewed in nature; (e) highlighted unprecedented research outcomes on costs; and (f) were comprising at least one or more demographic zones. Thus, the screening procedure facilitated the selection of 32 articles. Majority of research publications were excluded on the grounds if they (a) did not provide the detailed analysis of how costs were estimated; (b) were conference articles or posters; (c) only presented the costs of diabetes prevention; and (d) were published in non-peer-reviewed journals. The exploration includes those articles which highlight the cost burden of diabetes in India. Whilst performing the analysis, two interdependent excel spreadsheets were developed for data to be summarised. In the very first spreadsheet, a predefined category was used, viz. publication title/year, study type, location, diabetes type, methodology and findings. Relevant information is drawn out and presented in Table 1 , highlighting the study characteristics of the included articles. The second excel spreadsheet focuses its attention on the list of technical criteria applied to assess the quality of the articles incorporated in the review process. Copious checklist has been put forward for the quality assessment of the included studies and majority of them emphasise on the economic assessment, viz. cost analysis, cost-benefit analysis (CBA), health care utility analysis, etc. [27, 28] . Therefore, the quality indicators developed for the present study were grounded on the criterions suggested by prior literature [29] [30] [31] [32] . A symbol of (√) yes, (×) no and (±) moderately available was assigned to individual quality indicator. Each symbol was allocated with a score of 1, which leads to a maximum attainable score of 10 for each study reviewed. Hence, a complete detailed analysis of the parameters utilised is presented in Table 2 . The characteristics of the included thirty-two studies are presented in Table 1 were included. The cost of diabetes was estimated from various locations such as the south zone (n = 11), followed by the north zone (n = 8), the north-east zone (n = 1) and the west zone (n = 1). A large proportion of 11 studies (34%) were defined under India as a whole. Whilst conducting review studies, it is imperative to initially define the type, study interest, sample size, data source and outlook of the study. The included studies majorly focus on type 2 diabetes (n = 9), followed by both type 1 and type 2 studies (n = 8), 2 studies were identified under type 1 diabetes and only 1 study was acknowledged under gestational/foot ulcer category, whilst the remaining 12 studies did not define any diabetes type (Table 1 ). Of the total 32 studies, 94% of studies focus on general costs and the remaining 2 studies emphasise on foot ulcers and others. Whilst discussing the cost interests, the complications associated with diabetes were estimated by merely10 studies and the remaining 22 studies (69%) estimated the diabetes cost without any complications. Defining sample size is the utmost priority of the study, 27 studies (83%) of the total 32 studies have properly identified the sample size to be ≤ 100 respondents, only 2 studies specified the population size to be > 100 respondents and 3 studies (10%) did not define or provide the sample size. Under the source of the cost data section, 16 studies (50%) retrieved data on cost from the patients themselves; for 11 studies (34%), source of cost data was obtained from medical institutes; and the remaining 5 studies (16%) acquired the data on cost from publications. Studies on the economic burden of illness could be done through several perspectives, viz. household, patient, societal and governmental. In the particular study, the patient's perspective was most commonly The research question of the study was mentioned? Epidemiological definition such as type of diabetes (1 and 2) studied was provided? Complications associated with diabetes were clearly stated? The location of the study respondent was clearly defined? The sample size of the study was adequate? acknowledged by 19 studies (61%), 9 studies considered societal perspective, followed by government perspective for 7 studies and lastly, household perspective was adopted by 6 studies as highlighted in Table 1 . The quality of the included studies is broadly presented in Table 2 . For all 32 studies, research questions and findings were discussed and explained in a very well-defined manner. The presentation of the results was completely in synchronisation with the aim and conclusions derived from the reviewed articles. It was found that 60% (19) of the studies have comprehensively defined the epidemiological definition such as type of diabetes (type 1 and type 2). Limitations experienced by the majority of studies that hampered the quality of the reviewed articles were the absence of a broad definition of diabetes and a lack of adequate sample size. A major proportion of 25 studies (78%) did not extensively define diabetes and 18 studies (56%) moderately considered the sample size. For most of the reviewed articles, the sampling technique for data collection was addressed and only 1 study did not define the sampling technique. However, 56% (18) of studies lucidly defined the tools and technique employed in the reviewed articles and the remaining 14 studies moderately describe the tools and technique. A majority of 27 studies (84%) have properly classified the cost of diabetes and the remaining 5 studies defined moderately. Hence, based on quality index scores, the majority of the studies (n = 11) scored '6 Yes' on a 10-point scale. Interestingly, 5 studies attained a marginally higher score of '8 Yes' of the total 32 studies as presented in Table 2 . The economic burden of diabetes mellitus has led to numerous studies on the cost of illness. The cost exerted by diabetes can be categorised into three groups: direct cost, indirect cost and intangible cost [55, 56] . Direct cost includes both direct health care costs (diagnosis, treatment, care and prevention) and direct non-health care costs (transport, housekeeping, social service and legal cost) [1, 57] . Indirect cost includes cost for absenteeism, loss of productivity and disability [58, 59] . Lastly, intangible costs embrace cost for social isolation and dependence, low socio-economic status, mental health and behavioral disorder and loss of quality of life [56, 60, 61] . All twenty-one reviewed studies put forward data and statistics to evaluate per capita cost of individual/household at zone level and the remaining eleven studies highlighted the cost of diabetes at the national level (Table 3) . To have a clear insight on cost, the reviewed articles have been categorised into four different zones, viz. north zone, west zone, south zone and north-east zone. were lucidly defined? 9. Cost of diabetes was properly classified? The estimated annual direct cost was ₹ 7070/individual and indirect cost was ₹12,756 including productivity and income loss through illness. ---- The mean total cost of diabetes in India accounts to ₹7159/p.a. The mean direct cost of diabetes was ₹4724/-and indirect cost, viz. hospitalisation, was 2435/-p.a. (Some regional differences in patterns of expenditure exist, with patients in the west of India likely to spend 26% more on laboratory fees, check-ups and medicines than any other region.) ---- The mean annual direct cost of treatment was ₹8822/and 52% of amount is spent on drugs and medicines. The mean annual indirect cost of treatment was ₹3949/of which 91.3% was wage loss. ---- The total cost for diabetes management was ₹5041/p.a. of which ₹4282/was direct cost for the treatment of diabetes and ₹462/was spent on indirect cost. The total cost for treatment of diabetes with comorbidities was ₹9133/p.a. The direct cost with complications was ₹8185/p.a. and indirect cost amounts to be ₹508/p.a. ---- The mean direct cost of diabetes for consultation, lab investigation, medicines etc. was ₹9112/monthly, whereas indirect cost for outpatient care was ₹1166/monthly and indirect cost for inpatient care was ₹7068 per month. ---- The total average yearly direct cost was observed to be ₹7158/-. However, the mean direct cost for all patients with diabetes was ₹4724/p.a. Individuals with three or more comorbidities encountered 48% more cost of care, amounting to ₹10,593/annually. [50] Katam et al. 2016 The average total direct cost per patient annually was amounted to be ₹27,915/-. The highest portion of direct cost was spent on insulin and glucose test strips (40%). ---- [47] Khongrangjem et al. The total median cost of illness per month was ₹5375/-. Total cost was made up of ₹3816/direct cost and ₹1559/indirect cost. ---- [44] Kumar et al. 2008 The total mean evaluation of annual direct spending on ambulatory diabetes care was ₹6000/-. ---- [49] Kumar and Mukherjee The total direct expenditure incurred on diabetes was ₹76,779/p.a. and total indirect expenditure was ₹30,670/p.a. ---- Kumpatla et al. 2013 The total direct cost estimates without any complication were observed to be ₹4493/-. The total cost of expenditure with complication was ₹15,280/-. (cost for patients with foot complication was ₹19,020/-, also average cost for renal patients Under the north zone, 8 studies were included to calculate both direct and indirect costs of diabetes at the individual/household level (Fig. 1) . The median direct cost of diabetes is estimated to be ₹18,890/per annum, ranging from ₹999/to ₹1,09,344/- [19, 35, 39, 44, 46, [48] [49] [50] . The most commonly measured costing items under direct cost were expenditure on medicines (7 studies), diagnostic expenses (2 studies), transportation cost (1 study), hospitalisation (2 studies) and consultation fee (3 studies). The median indirect cost of diabetes for the north zone was evaluated to be ₹18,146/per annum, ranging from ₹4642/ -to ₹98,808/- [19, 35, 46, 49] . For all indirect cost studies, costing items, viz. wage loss and leisure time forgone, were used majorly. South zone includes 11 studies, majorly from Karnataka state (6 studies), followed by Tamil Nadu (4 studies) and Andhra Pradesh (1 study). The median direct cost was assessed to be ₹10,585/per annum (Fig. 1) , ranging from ₹377/to ₹21,258/per annum [2, 6-9, 33, 37, 38, 40, 42, 45] . Direct costing items, viz. medicine cost (9 studies), consultation fees (4 studies) and hospitalisation (3 studies), were used in the reviewed article. The median indirect cost of diabetes was ₹1198/per annum, ranging from ₹462/to ₹3572/per annum with major cost items such as monitoring cost (1 study), absenteeism (3 studies) and impairment (1 study) [7-9, 33, 37] . Under the north-east and west zone, only one-one study was observed, to evaluate the direct and indirect cost of Author Publication year was ₹12,690/followed by 13,135/-for cardiovascular disease.) [36] Ramachandran 2007 The average inpatient and outpatient cost of diabetes is ₹7505/p.a. and ₹3310/p.a. ---- [34] Ramachandran et al. The total median direct expenditure on health care was ₹8130/p.a. ---- The mean cost per hospitalizations was ₹5925/p.a. for diabetes. ---- Rayappa et al. 1999 The direct annual cost (incl. hospital, test, monitoring etc.) was ₹15,460/and indirect annual cost was ₹3572/-. The total direct cost (incl. drugs, tests, consultation, hospital, surgery, transport) was ₹4510/half yearly. The total direct cost (drugs and medicine) for diabetes patients was ₹3241 p.m. ---- [46] Thakur et al. 2017 The mean annual direct expenditure for diabetes care was ₹9832 and indirect cost was ₹5622. ---- [52] Tharkar et al. The total direct cost for hospitalisation was ₹14,000 p.a. The total direct cost for hospitalisation with comorbidities was ₹19,000/p.a. [22] Tharkar et al. 2010 The median annual direct cost associated with diabetes care was ₹25,391 and indirect cost was ₹4970, respectively. ---- diabetes at the individual/household level [47, 51] . The median direct cost of diabetes for north-east was evaluated to be ₹45,792/per annum and ₹8822/per annum was observed for the west zone (Fig. 1) . Commonly estimated costing items were surgical procedures, expenditure on drugs/medicines, clinical fees, etc. The median indirect cost estimated for the north-east zone was ₹18,707/per annum and ₹3949/per annum was analysed for the west zone. Indirect costing items identified for both reviewed studies were loss of wage, spendings on health class, travelling expenditure and spendings on diet control. Lastly, 11 studies were incorporated to estimate the cost of diabetes for India as a whole at the individual/ household level [5, 20, 22-24, 34, 36, 43, 51-53] . The median direct cost of diabetes for India as a whole was ₹9996/per annum, ranging from ₹4724/to ₹25,391/per annum. Also, the median indirect cost of diabetes at the individual/ household level was estimated to be ₹5237/per annum, ranging from ₹2435/to ₹12,756/annually ( Figs. 1 and 2 ). Diabetes mellitus is associated with a large number of serious and chronic complications, which act as a major cause of hospitalisation, morbidity and premature mortality in diabetic patients [2, 7, 8, 42] . Diabetes mellitus is commonly associated with chronic complications both macrovascular and microvascular origin [2, 3] . Microvascular complications of diabetes mellitus include retinopathy, autonomic neuropathy, peripheral neuropathy and nephropathy [3, 53] . The macrovascular complication of diabetes mellitus broadly includes coronary and peripheral arterial disease [2, 7] . Of the total reviewed studies, only 10 studies estimated the cost of complications associated with diabetes (Table 3) . A couple of studies on diabetes assessed the cost of illness to be 1.4 times higher for individuals with complications as exhibited in Table 3 [8, 52] . A similar study by Sachidananda et al. [42] concluded that the cost of diabetes is 1.8 times higher for complicated non-hospitalised patients and 2.4 times higher for complicated hospitalised patients. Kapur [38] inferred that individuals with three or more comorbidities encounter 48% more cost of care, amounting to ₹10,593/annually. According to Cavanagh et al. [5] , India is the most expensive country for a patient with a complex diabetic foot ulcer, where 68.8 months of income was required to pay for treatment. Three reviewed studies incorporated in the study estimated the cost of individual/household with both macrovascular and microvascular complications [2, 7, 53] Kansra [54] , as suggested by Moher et al. [25] the cost of illness prompted by renal (kidney) complication [2, 53] . Lastly, Eshwari et al. [9] estimated the total cost for the treatment of diabetes with comorbidities was ₹9133/annually. Direct cost with complications was ₹8185/per annum and indirect cost amounts to be ₹508/annually. Rising menace of diabetes has been a major concern for India. With a frightening increase in population with diabetes, India is soon going to be crowned as 'diabetes capital' of the world. A swift cultural and social alteration, viz. rising age, diet modification, rapid urbanisation, lack of regular exercise regimen, obesity and a sedentary lifestyle, will result in the continuous incidence of diabetes in India. The primary objective of this article is to detect and capture the evidence from published literature on the per capita cost at the individual/household level for both direct and indirect costs of diabetes in India which are available and published since 1999. Of the total 412 records, 32 studies were identified to meet the inclusion criterion. Therefore, the findings of the present study suggest that per annum median direct and indirect cost of diabetes at the individual/household level is very colossal in India. A large proportion of health care cost is confronted by the patients themselves, which affects the fulfilment of health care because of financial restraints [62] . The proportion of public health expenditure by the Indian government is the lowest in the world. As a consequence, out-of-pocket (OOP) spending constitutes to be 70% of the total health expenditure. Hence, financing and delivering health care facilities in India is majorly catered by the private sector for more than 70% of diseases in both rural and urban areas [24] . Direct cost items (expenditure on medicines, diagnostic expenses, transportation cost, hospitalisation and consultation fee) and indirect cost items (loss of wage, spendings on health class and travelling expenditure) were most commonly reported costing items in the present study [8, 9, 19, 37, 46, 48] . Most of the reviewed studies on the cost of diabetes highlighted expenditure on drugs/medicine as the foremost costing item which accounts for a significant share of all direct costs. The finding of the present study is consistent with Yesudian et al. [62] , 'cost on drugs constitutes 50% of the total direct costs'. The majority of the reviewed articles included in the study justify that the primary cause for such abnormal costs of medicines is the common practice adopted by physicians to prescribe brandnamed medicines, rather than generic medicines. In context to the quality of tools and techniques incorporated by the included studies, a large number of articles (56%) witnessed to acknowledge the standards of tools and techniques. Similarly, the classification of the cost of diabetes was also determined by the majority of reviewed articles (27 articles) . But the absence of a comprehensive definition of diabetes and a small size of individuals/ households produce dubiousness about the standards or quality of the study. Hence, the limitations experienced by the majority of reviewed articles hampered the quality of the present study. Thus, it is beneficial to develop and suggest standard procedures and framework to conduct a comprehensive and exhaustive study on the cost of diabetes. The present study holds few limitations. Primarily the exclusion of the relevant articles presented as conference papers and those studies published under nonpeer-reviewed journals. With the omission of the above literature, some biasness might have been introduced into the review process. Furthermore, the major limitation of the present study is the non-availability of published articles under the central and east zone of India. Also, the studies published under the north-east zone and west zone were only one. Lastly, the heterogeneity in material and methodology used in cost estimation are not analogous. As a consequence, conducting a metaanalysis is not feasible. The above discussion highlighted a huge economic burden of diabetes in India and variations were recorded in the different zones. It was observed that the cost of drugs/medicines accounts for a major burden of the cost of diabetes. The study suggested few policy interventions to cope with the high economic burden of diabetes. There is a dire need in the country to arrange awareness programmes on diabetes and associated risk factors. The menace of diabetes can be controlled by devising new health care policies, introducing new generic medicines and taxing alcohol/tobacco. Diabetes is a lifestyle disease so along with the above measures, a change in dietary habits, physical activity, beliefs and behavior can reduce its economic burden. Conflict of interest The authors declare that they have no conflict of interest. Ethical approval The study is a review-based study, so it does not contain any studies with animals. The present study only reviews those studies which contain individual's performance. Informed consent For the present study, it is not necessary to obtain any consent. Diagnosis and classification of diabetes mellitus The costs of treating long term diabetic complications in a developing country: a study from India Diabetes mellitus and its complications in India WHO Multinational Study Group. Mortality and causes of death in the WHO Multinational Study of Vascular Disease in Diabetes Cost of treating diabetic foot ulcers in five different countries Dispensing patterns and cost of glucoselowering therapies in diabetes mellitus patients at a tertiary care hospital in Southern India Health-care cost of diabetes in South India: a cost of illness study Assessment of cost of illness for diabetic patients in South Indian tertiary care hospital Annual cost incurred for the management of type 2 diabetes mellitus-a communitybased study from coastal Karnataka Trends in prevalence of diabetes in Asian countries Time use and physical activity: a shift away from movement across the globe Difference in prevalence of diabetes, obesity, metabolic syndrome and associated cardiovascular risk factors in a rural area of Tamil Nadu and an urban area of Delhi Economic vulnerability to health shocks and coping strategies: evidence from Andhra Pradesh, India. Health Policy Plan Prevalence of risk factors for non-communicable diseases in rural and urban Tamil Nadu International Diabetes Federation: IDF Diabetes Atlas IDF Diabetes Atlas: global estimates of diabetes prevalence for 2017 and projections for 2045 The economic burden of diabetes in India: a review of the literature Awareness about diabetes among adolescents of Mangalore Economic burden of diabetes among women: a comparison of outpatient and inpatient care Problems associated with diabetes care in India Current scenario of diabetes in India The socioeconomics of diabetes from a developing country: a population based cost of illness study Socio-economic inequalities in the financing of cardiovascular and diabetes inpatient treatment in India Cost of diabetic care in India: an inequitable picture Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews Methodological considerations in cost of prostate cancer studies: a systematic review Cost of illness for bipolar disorder: a systematic review of the economic burden Cost-of-illness methodology: a guide to current practices and procedures Cost of illness studies: what is good about them? Cost-of-illness studies Cost of diabetes mellitus in Africa: a systematic review of existing literature Economic cost of diabetes care: the Bangalore urban district diabetes study Increasing expenditure on health care incurred by diabetic subjects in a developing country: a study from India Cost of ambulatory care of diabetes mellitus: a study from north India Socio-economic burden of diabetes in India Excess cost burden of diabetes in Southern India: a clinicbased, comparative cost-of-illness study Economic analysis of diabetes care Burden of healthcare utilization and out-of-pocket costs among individuals with NCDs in an Indian setting Expenditure on health care incurred by diabetic subjects in a developing country-a study from southern India Economic burden of diabetes in urban Indians Health care cost incurred by patients of diabetes mellitus in a tertiary care hospital setting in Coastal Karnataka district Global policy: aspects of diabetes in India Direct cost of ambulatory care of type 2 diabetes in the middle and high income group populace of Delhi: the DEDICOM survey Costs incurred by families having type 1 diabetes in a developing country-a study from southern India Expenditure pattern on diabetes care: a community based longitudinal study in resettlement colony of East Delhi Cost of illness (COI) of type-II diabetes mellitus in Shillong, Meghalaya Drug prescription patterns and cost analysis of diabetes therapy in India: audit of an endocrine practice Economic impact of type-2 diabetes mellitus on households in Hisar district of Haryana state High direct costs of medical care in patients with type 1 diabetes attending a referral clinic in a government-funded hospital in northern India The economic burden of diabetes in India: results from a national survey Cost of medical care among type 2 diabetic patients with a co-morbid conditionhypertension in India Direct costs associated with chronic kidney disease among type 2 diabetic patients in India Factors influencing medical tourism in India: a critical review Costs of diabetes The economic burden of depression in Sweden from Economic costs of diabetes in the US in 2002 A prospective study of outcomes, healthcare resource utilization, and costs associated with postoperative nosocomial infections The prevalence of multi-morbidity in primary care and its effect on health care utilization and cost The burden of epilepsy for the patient: the intangible costs Economics of psychosocial factors in patients with cardiovascular disease The economic burden of diabetes in India: a review of the literature Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations 


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   key: cord-352544-7b6btzrx authors: Liu, Zhelong; Bai, Xi; Han, Xia; Jiang, Wangyan; Qiu, Lin; Chen, Shi; Yu, Xuefeng title: The association of diabetes and the prognosis of COVID-19 patients: a retrospective study date: 2020-08-25 journal: Diabetes Res Clin Pract DOI: 10.1016/j.diabres.2020.108386 sha: doc_id: 352544 cord_uid: 7b6btzrx Abstract Aims This study evaluated the impact of previous glycemic control and in-hospital use of antidiabetic/antihypertensive drugs on the prognosis of COVID-19 patients with diabetes. Methods In this retrospective cohort study, consecutive inpatients with laboratory confirmed COVID-19 were enrolled from Tongji Hospital (Wuhan, China). Patients without diabetes were matched to those with diabetes based on age, sex, and comorbidities. All patients were followed up to a clinical endpoint (discharge, worsening including transferring to ICU or immediate death). Data and outcomes were extracted from medical records and analyzed. Results 64 patients with pre-existing diabetes were included in this study, with 128 matched patients without diabetes included as a control group. Patients with diabetes had a higher rate of worsening (18.8% versus 7.8%, p=0.025). Multivariable regression showed increased odds of worsening associated with previous glycemic control reflected by HbA1c (odds ratio 3.29, 95% CI 1.19-9.13, p=0.022) and receiver-operating characteristics (ROC) curve identified HbA1c of 8.6% (70 mmol/mol) as the optimal cut-off value. Univariate analysis demonstrated the in-hospital use of antidiabetic/antihypertensive drugs were not associated with a higher risk of worsening. Conclusions COVID-19 patients with diabetes had a higher risk of worsening, especially those with poorly-controlled HbA1c, with an optimal cut-off value of 8.6%. The in-hospital use of antidiabetic/antihypertensive drugs were not associated with increased odds of worsening in patients with diabetes. Since Dec 2019, the novel coronavirus disease 2019 has spread rapidly around the world and infected more than 10 million people hitherto [1] . The pathogen was identified as a novel, highly contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which can invade the human body through angiotensinconverting enzyme 2 (ACE-2) [2] . The clinical manifestations of COVID-19 include fever, dry cough, dyspnea, myalgia, fatigue etc, and severe cases can rapidly develop into acute respiratory distress syndrome, septic shock, and multiple organ dysfunction syndrome [3] . Recent studies have shown that diabetes mellitus (DM) is one of the most common comorbidities of COVID-19, with a prevalence ranging from 5.3% to 58.0% [4] [5] [6] . Diabetes has been associated with an increased mortality in previous viral epidemics, such as the outbreak of SARS-CoV-1 and Middle East respiratory syndrome coronavirus [7, 8] . Similar conclusions were reported in the pandemic of SARS-CoV-2. Some studies have suggested that diabetes is a risk factor for the poor prognosis of COVID-19 [4, 9, 10] , while some studies reported that patients with diabetes seemed not to have a higher mortality risk [11, 12] . Data regarding the impact of diabetes on the prognosis of COVID-19 patients are scant and controversial. Good glycemic control should be the most important for patients with diabetes during the COVID-19 infection as it has been shown to improve the innate immune system [13, 14] . Data from other viral epidemics such as SARS and influenza H1N1 has demonstrated that patients with poor glycemic control have a higher mortality risk [7, 15] . Unfortunately, the previous studies mostly focused on the impact of diabetes, as a comorbidity, on the prognosis of COVID- 19 . Despite a few studies reported that COVID-19 patients with poorly controlled fasting blood glucose in hospital were associated with higher mortality [16] , there is still a lack of information on the impact of previous glycemic control on the prognosis of COVID-19 patients with diabetes. In addition, previous studies have reported that metformin could increase ACE-2 expression and improve its stability by impeding its ubiquitination and proteasomal degradation [17] . Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin II receptor 1 blockers (ARB) also have been considered as a link between COVID-19 and diabetes because they are widely used in patients with diabetes [18] . However, there are still no solid evidences demonstrating the impact of these medications on the prognosis of this population. In this report, we aimed to evaluate the prognosis of COVID-19 patients with diabetes and the impact of previous glycemic control on it. Besides, the influence of the commonly used antidiabetic and antihypertensive drugs on the prognosis of patients with diabetes was also explored. [19] . Patients with diabetes were designated according to the patient's medical history. Then the patients without diabetes were matched (2:1 ratio) to the patients with diabetes based on age, sex, and comorbidities (hypertension, hyperlipemia, chronic renal diseases). The study was approved by the Ethics Committee of Tongji Hospital (TJ-IRB20200404). Written informed consent forms were waived in the urgency of pandemic. A trained team of physicians extracted the epidemiological, demographic, clinical, laboratory, treatment, and prognosis data from electronic medical records. The demographic characteristics, comorbidities, clinical symptoms, symptoms from onset to admission, vital signs, laboratory findings, antidiabetic and antihypertensive drugs used prior to admission and during hospitalization, and outcomes were collected. Most of the clinical data used in our study were collected from the first day of admission unless otherwise stated. Comorbidities were determined based on the patient's selfreport on admission. The glycated hemoglobin A1c (HbA1c) and the maximum of the blood glucose (BG) in-hospital were used to reflect the previous and in-hospital glycemic control, respectively. All data were double-checked by different researchers to guarantee the accuracy. All patients were followed up to a clinical endpoint (discharge, worsening including transferring to intensive care unit (ICU) or immediate death). Patients who transferred to ICU or died immediately before transferring to ICU were classified as the worsening group. Continuous and categorical variables were described as median (interquartile range [IQR] ) and number (%), respectively. Continuous variables between groups were compared by the Mann-Whitney U test, and categorical variables were compared by Chi-square or Fisher's exact test where appropriate. Binary logistic regression models were used to evaluate the impact of the previous and in-hospital glycemic control on the outcomes of the patients with diabetes, and three models were constructed to adjust potential confounding factors. Model 1 explored the risk factors associated with worsening by a univariate analysis, which included HbA1c, maximum of the BG in-hospital, age, sex, smoking, comorbidities other than diabetes, white cell count, the percentage of neutrophils, lymphopenia, alanine aminotransferase, aspartate aminotransferase, γ -glutamyl transferase, creatinine, C-reactive protein (CRP), D-dimer, N-terminal brain natriuretic peptide precursor (NT-proBNP), cardiac troponin I (cTnI), prothrombin time, total cholesterol, triglyceride, interleukin-6, tumor necrosis factor-α. Model 2 included HbA1c and the maximum of the BG in-hospital for a multivariate logistic regression analysis. On the basis of model 2, the variables with a P value <0.05 in the univariate analysis were further added for a multivariate analysis in the model 3. Considering the limited number of the patients in the worsening group, three variables, which included lymphocyte, CRP and prothrombin time, were added in the model 3 to avoid over-fitting. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of the HbA1c level on the prognosis of the patients with diabetes. When we evaluated the association between the use of each antidiabetic or antihypertensive drug and the outcomes, due to the limited number of patients in each subset, logistic regression model was used and only glucose, HbA1c at admission or maximum of the glucose inhospital were adjusted to avoid over-fitting. The results were shown in odds ratio (OR) and 95% confidence interval (CI). A two-sided P value < 0.05 was considered statistically different. All statistical analyses were performed with SPSS, version 24.0 (IBM SPSS). A total of 64 confirmed COVID-19 patients with pre-existing DM were included in this study (Table 1) both groups were fever and cough, followed by fatigue and diarrhea ( Table 1 ). The patients with diabetes reported a significantly higher incidence of fever (76.6% versus 61.7%) compared to the group without diabetes. Laboratory findings on admission and clinical outcomes of both groups are summarized in Table 2 . The rate of disease worsening during hospitalization was significantly higher in the patients with pre-existing DM compared to the patients without diabetes (18.8% Complete data collected from 64 patients with diabetes (12 in the worsening group, and 52 in the discharge group) were included in the logistic regression models (Table 3 ). In the univariable analysis (Model 1), HbA1c, maximum of the BG in-hospital, lymphopenia, the percentage of neutrophils, CRP and prothrombin time were associated with worsening. In the model 2 included HbA1c and the maximum of the BG in-hospital, only HbA1c was associated with increased odds of worsening. When adjusting for lymphopenia, CRP and prothrombin time, HbA1c was still associated with increased odds of worsening. Using disease worsening as the end point, ROC curve analysis was used to identify the optimal HbA1c cutoff value, which was 8.6% (70 mmol/mol) (Figure 1 ). With this value, the area under the ROC curve was 0.90 (95% CI, 0.83-0.98, p < 0.001), and the sensitivity and specificity for predicting disease worsening in the patients with diabetes were 100.0% and 82.7%, respectively. For each laboratory index, patients were divided into 2 groups for further analysis (Table 4 ). Compared to the HbA1c well-controlled patients, the poorly-controlled patients presented higher white cell count and the percentage of neutrophils. Also, the incidence of lymphopenia was higher in the poorlycontrolled patients. Levels of the maximum of the BG in-hospital, hemoglobin, triglyceride, urea nitrogen, prothrombin time and cTnI were clearly elevated in the poorly-controlled patients compared with the well-controlled patients. This retrospective cohort study have 3 novel findings with important implications for the COVID-19 patients with diabetes. First of all, not only did we find that COVID-19 patients with pre-existing DM had an increased risk of disease worsening, but poor previous glycemic control, which was reflected by HbA1c, was associated with higher odds of disease worsening. Second, to our knowledge, this was the first study investigating the prognostic value of HbA1c in the COVID-19 patients with diabetes, and a HbA1c level of 8.6% (70 mmol/mol) was the optimal cutoff value. Furthermore, we found that α-glucosidase inhibitors and CCBs use were associated with reduced odds of disease worsening. Metformin, insulin, ACEIs/ARBs and statins were not Previously, the prognosis of COVID-19 patients with pre-existing DM has been reported. The majority of the studies demonstrated that diabetes was an important risk factor for the progression or mortality in COVID-19 [4, 9, 10] , while some reported that COVID-19 patients with diabetes seemed not to have a higher mortality risk [11, 12] . A recent meta-analysis involving 4 studies suggested that COVID-19 patients with diabetes had an increased risk of ICU admission and mortality [20] , which was consistent with the results in our study. It is worth noting that the judgement of preexisting diabetes was based on the patient's self-report at admission, which could lead to the underdiagnosis of diabetes in the control group. In fact, the median level of HbA1c in the control group was 6.3%, which was above the normal upper limit of HbA1c (6.0%). Thus, although our results showed an increased risk of disease worsening in COVID-19 patients with diabetes, the risk might still be underestimated. HbA1c is considered to be a good indicator reflecting long-term glycemia [21] . Previous studies have reported that patients with poor HbA1c control were more susceptible to infections, such as the infections of Chlamydia pneumoniae, hemolytic streptococci groups B, G, Klebsiella pneumoniae, Mycobacterium tuberculosis, and exhibited worse prognosis compared to the patients with well HbA1c control [22] [23] [24] [25] . Besides, chronic hyperglycemia was thought to downregulate ACE-2 expression, making cells susceptible to the damage of SARS-CoV-2 [26] . However, to our knowledge, the association between HbA1c level and the prognosis of COVID-19 patients with diabetes has not been explored. Our study found that among COVID-19 patients, those with poor HbA1c control had a higher risk of disease worsening, with an optimal cut-off value of 8.6% (70 mmol/mol), demonstrating the importance of previous glycemic control. Furthermore, we compared the clinical characteristics of the HbA1c well-controlled group with the poorly-controlled group. The HbA1c poorlycontrolled patients presented a higher incidence of lymphopenia (71.4% versus 44.2%) compared to the well-controlled patients. Also, the levels of the percentage of neutrophils, prothrombin time and cTnI were significantly elevated in the poorlycontrolled group. The changes in these clinical indicators were consistent with those in the COVID-19 severe cases that have been reported previously [4, 11, 27] , suggesting that the higher risk of disease worsening in the poorly-controlled group might be associated with the changes in these clinical indicators in addition to the poor glycemic control. The association between the in-hospital use of common antidiabetic/antihypertensive drugs and the prognosis of the COVID-19 patients with diabetes was also explored in this study for the first time. The results demonstrated that α-glucosidase inhibitors and CCBs use were associated with a lower risk of disease worsening, and no significant associations were observed between the use of metformin, insulin, ACEIs/ARBs, statins and disease worsening after adjusting for glucose, HbA1c at admission and maximum of the glucose in-hospital. Previous studies demonstrated that ACE-2 Ser680 residue could be phosphorylated to improve the stability and increase the expression of ACE-2 in human umbilical vein endothelial cells by the 5′-AMP-activated protein kinase, which was the molecular effector of the majority of metformin's pharmacological actions [17] . Special considerations were also recommended on the use of metformin due to the lactic acidosis associated with it [26] . In addition, previous studies reported that ACEIs/ARBs could upregulate the ACE-2 expression, which might facilitate the entry and proliferation of SARS-CoV-2 [13, 28] . Thus, there are concerns about the safety of using ACEIs/ARBs in patients with diabetes. Our results demonstrated that there were no significant associations between the use of metformin, insulin, α-glucosidase inhibitors, ACEIs/ARBs, CCBs, statins and increased odds of disease worsening. Even the use of α-glucosidase inhibitors and CCBs were significantly associated with decreased odds of disease worsening. Although the potential bias of reverse causation cannot be ruled out, our results at least suggested that the use of these drugs were not associated with a higher risk of disease worsening. However, considering the risk of acute metabolic decompensation caused by metformin in COVID-19 patients with severe symptoms as well as the fact that the maximum of the in-hospital BG alone cannot fully reflect the in-hospital glycemic control, the safety of the in-hospital use of metformin needs more studies to explore. There were some limitations of our study. First, the interpretation of our results might be limited by the sample size. Second, owing to the retrospective design of the study, the lack of data didn't allow us to analyze the type of DM, disease course and mean inhospital BG. Third, due to the lack of mean in-hospital BG resulting from the urgency of pandemic, only the maximum of the in-hospital BG could be used to reflect the inhospital glycemic control, which could reduce the convictive power of the conclusions about the safety of antidiabetic/antihypertensive drugs. In the urgent conditions, medical history was not taken in detail and some laboratory examinations were not performed in all patients. COVID-19 patients with pre-existing DM had an increased risk of disease worsening, especially those with poorly-controlled HbA1c, with an optimal cut-off value of 8.6% (70 mmol/mol). The in-hospital use of common antidiabetic/antihypertensive drugs were not associated with a higher risk of disease worsening in COVID-19 patients with diabetes. Ethical approval for this study was granted by the Ethics Committee of Tongji Hospital (TJ-IRB20200404). Written informed consent was waived due to the urgency of pandemic. The dataset used during the current study are available from the corresponding author on reasonable request. None. All authors read and approved the final manuscript. SC and XY designed the study. ZL and XH collected data. XB conducted the analysis and wrote the first draft. WJ and LQ finalized the manuscript. The corresponding authors attests that all listed authors meet the authorship criteria and that no others meeting the criteria have been omitted. Table 1 Demographics and baseline characteristics of COVID-19 patients Abbreviations: ACEI, Angiotensin-converting enzyme inhibitor; ARB, Angiotensin II receptor 1 blocker. Figure 1 The predictive value of the HbA1c level for the worsening among COVID-19 patients with diabetes. 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Diabetes research and clinical practice Clinical considerations for patients with diabetes in times of COVID-19 epidemic Prevalence of Diabetes in the 2009 Influenza A (H1N1) and the Middle East Respiratory Syndrome Coronavirus: A Systematic Review and Meta-Analysis Association of Blood Glucose Control and Outcomes in Patients with COVID-19 and Pre-existing Type 2 Diabetes AMP-activated Protein Kinase Phosphorylation of Angiotensin-Converting Enzyme 2 in Endothelium Mitigates Pulmonary Hypertension Should anti-diabetic medications be reconsidered amid COVID-19 pandemic? Diabetes research and clinical practice New coronavirus pneumonia prevention and control program Diabetic patients with COVID-19 infection are at higher risk of ICU admission and poor short-term outcome Screening for diabetes in Indigenous populations using glycated haemoglobin: sensitivity, specificity, post-test likelihood and risk of disease. Diabetic medicine : a journal of the Chlamydia pneumoniae infection in adolescents with type 1 diabetes mellitus Impact of diabetes and poor glycaemic control on risk of bacteraemia with haemolytic streptococci groups A, B, and G Impact of glycemic control on capsular polysaccharide biosynthesis and opsonophagocytosis of Klebsiella pneumoniae: Implications for invasive syndrome in patients with diabetes mellitus The correlation between CT features and glycosylated hemoglobin level in patients with T2DM complicated 20 with primary pulmonary tuberculosis. Infection and drug resistance 11 Practical recommendations for the management of diabetes in patients with COVID-19. The lancet Clinical features and treatment of COVID-19 patients in northeast Chongqing Angiotensin-converting enzyme inhibitors and angiotensin receptor blockers may be harmful in patients with diabetes during COVID-19 pandemic Poor previous glycemic control, which was reflected by HbA1c, was associated with higher odds of disease worsening, which included transferring to ICU or immediate death A HbA1c level of 8.6% (70 mmol/mol) was the optimal cutoff value for the prognosis of COVID-19 patients with diabetes The in-hospital use of common antidiabetic/antihypertensive drugs were not associated with a higher risk of disease worsening in COVID-19 patients with diabetes Not applicable. 


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   key: cord-027036-lvcxrmih authors: Shaw, Ken title: The impact of diabetes on COVID‐19 infection date: 2020-06-09 journal: nan DOI: 10.1002/pdi.2272 sha: doc_id: 27036 cord_uid: lvcxrmih nan gence of this current novel coronavirus pandemic (SARS-CoV-2/ COVID-19) from Wuhan, China, it has become rapidly apparent that those with known preceding comorbidities are much more likely to develop life-threatening complications of pneumonia and acute respiratory distress syndrome. Not unexpectedly, diabetes has been identified as posing a particular adverse risk, along with chronic renal and coronary heart disease, and such surrogate risk indicators as obesity and hypertension. Actual susceptibility to infection with diabetes may be argued, but infection once acquired is likely to be more severe and prolonged, determined by a number of factors, including duration of diabetes, the presence of diabetes-related complications and the level of glycaemic control. Sub-optimal blood glucose levels, compounded by the adverse vicious cycle of response to infection, increase vulnerability and adverse outcome. For a comprehensive review as to how the immune system may be disturbed with diabetes, the relevant chapter, 'Infection and Diabetes', in Joslin's Diabetes Mellitus 1 is to be recommended. For example, studies are described reporting defects of cell-mediated immunity and diminished lymphocyte transformation response in people with poorly-controlled diabetes, while impaired leucocyte function, the first line of defence against secondary bacterial infection, can be demonstrated from observation of reduced phagocytic activity with increasing levels of blood glucose. 2 Such disturbances of immune function are very likely to have significant impact on the outcome of COVID-19 infection complicated by diabetes. Furthermore, it has been suggested that increased glucose concentrations in airway secretions may expose pulmonary epithelial cells to greater viral replication and consequent pneumonitis. 3 Although criticism has been levelled concerning the transparency of the early coronavirus epidemic experience in China, several preliminary clinical and epidemiological papers, summarised in a recent Practical Diabetes editorial, 4 have achieved rapid publication 5-7 primarily listing diabetes simply as an adverse comorbidity, more prevalent in severe cases and with non-survivors. These early reports of COVID-19 infection included observations of 52 critically ill adult patients with coronavirus pneumonia admitted to the ICU at the Wuhan Jin Yin-tan hospital, where diabetes was found in twice the number of individuals who died compared to those who survived (22% vs 10%). 5 This outcome has since been replicated on a wider scale from 552 hospitals across China 6 where, in a total of 1099 patients with established COVID-19 infection, diabetes was present in 7.4% of cases overall, but recorded in a significantly greater proportion of those with severe compared to non-severe disease (16.2% vs 5.7%). A small sample analysis of 26 fatalities reported diabetes in 42.3% of cases. 7 Further reports from Wuhan have since been published, with continued indication of diabetes as a risk factor for the progression and prognosis of COVID-19 infection. One study 8 has observed that 14% of cases had diabetes without any other comorbidities, but nonetheless these individuals were at much higher risk of developing severe pneumonia, excessive release of inflammatory bio-markers and increased hypercoagulability. This 'inflammatory storm' was associated with a more rapid deterioration of illness and a significantly higher mortality rate. From analysis 9 of 150 patients, predictors of fatal outcome included older age, the presence of other underlying diseases, the onset of secondary infection and elevated inflammatory markers. In 68 fatal cases, five (7%) patients died with myocardial damage, described as 'fulminant myocarditis' consequent to the 'cytokine storm'. Working in central London as a junior doctor during the 1969 Hong Kong Flu pandemic, one recollects that deaths in young individuals were often attributed to viral myocarditis. It is a salutary reflection as to how diabetes has exploded in this modern age, barely recognised as a clinical issue 50 years ago. In the western world, the University Hospital of Padua, at the epicentre of the outbreak in Italy, 10 reports that 35.5% of patients dying from COVID-19 infection had diabetes, compared to a matched population prevalence of 20.3%, while in preliminary estimates from the USA, 11 based on data from 122,653 persons with confirmed COVID-19 disease, diabetes proved to be the most significant medical comorbidity: 10.9% of total; 24% of those hospitalised and 32% of those admitted to the ICU. So far data for the UK are limited. However, the Office of National Statistics has reported 12 that in England and Wales 91% of those dying from COVID-19 infection had at least one pre-existing condition, including diabetes. More specifically, statistics from NHS England 13 for the period 31 March to 12 May 2020 record that of 22,332 COVID-19 deaths in hospital, 5873 (26%) had diabetes, a comparable proportion to New York City, with diabetes identified in 25% of patients hospitalised with COVID-19 infection. 14 Parallels have been drawn between this current coronavirus pandemic and the global Spanish Influenza pandemic of 100 years ago, but the concept of managing comorbidities, other than post-war malnutrition, would not have been foremost in mind at that time. Diabetes was, however, very much a consideration with the Swine Flu pandemic of 2009, when contingency planning and management guidelines were issued. 15, 16 Even then it was recognised that people with diabetes were potentially six times more likely to require hospitalisation during an influenza epidemic. 17 However, circumstances are different now, with no natural innate COVID-19 immunity in the population and a preventative vaccination programme yet to be developed. Recognising that some people may be more seriously vulnerable to infection, the UK government identified certain groups, primarily those with potential immune deficiency or with severe respiratory conditions, and advised that they self-isolate at home for 12 weeks. Although diabetes was not included in this list, people with diabetes have nonetheless been encouraged to take particular care with precautionary measures such as social distancing and relative self-isolation. The principles of diabetes management with infection remain relevant ('sick-day rules'). Under these circumstances people with diabetes may well feel anxious, with concerns about their diabetes control, availability of medical supplies and their access to expert advice. Guidance for people with diabetes has been made available online from organisations such as Diabetes UK 18 and JDRF, 19 and similarly for health care professionals from specialist bodies including the Association of British Clinical Diabetologists, 20 the US Endocrine Society jointly with the University of Leeds, 21 and an international perspective from the National Diabetes Foundation of India. 22 The latest (19 March 2020) clinical guide for the management of people with diabetes during the coronavirus pandemic has been issued jointly from the Royal College of Physicians, ABCD and the NHS, 23 while a National Diabetes Inpatient COVID Response Team has provided advice 24 on maintaining essential elements of the diabetes service, and collating shared experience to learn from these unprecedented circumstances. Education programmes in self-management, especially what to do in the event of acute illness, should be returning the desired dividend, but specialist advice must continue to be available for people in difficulties with their diabetes control. For instance, immediate facility will need to be in place to initiate insulin therapy for those with type 2 diabetes previously bordering on the edge of acceptable control on maximum oral hypoglycaemic agents. With the Swine Flu pandemic a five-to 10-fold increase in new case insulin demand was anticipated, and it has to be assumed the same need will arise with this pandemic; important data to be analysed in due course. At the time of writing, the peak rate of those infected, the numbers hospitalised and sadly the case-fatalities in the UK has yet to be reached, with measures still in place to suppress virus transmission and lessen pressures on the NHS. Inevitably, questions concerning easing of current restrictions raise issues as to whether there is sufficient acquired immunity in the population -present indication is that still is a low proportion -or whether that can only be achieved once an effective vaccination programme has been developed. It is possible that countries where a speedier response was initiated at the outset of the epidemic, have been in a better position to see restrictions lifted. Having gained previous experience with the former SARS-CoV and MERS-CoV coronavirus pandemics, Singapore has been cited as an exemplary model of management, being wellprepared in terms of pre-planning and rapid implementation of control measures, quarantining of infected individuals and family, along with early school closure and workplace distancing. 25 Based on personal observation, as a visitor at the time, everyone on airport arrival and at entry to public buildings, was subject to infra-red thermal scanning and if febrile, individuals were immediately isolated with rigorous contact tracing. Seemingly an effective measure -was this a missed opportunity in the UK? Furthermore, the addition of extensive antigen testing for infected persons and in particular of asymptomatic contacts appeared crucial to early success in controlling the outbreak, thereby facilitating an earlier return to post-epidemic normality, albeit with a small secondary wave relapse attributed to returning nationals, since similarly reported in China. At present uncertainty prevails, particularly for those in recognised vulnerable groups, such as diabetes. Without a reliable antibody test, many if not most people will be unsure as to their immune status, and indeed for those who have recovered from overt coronavirus infection, the degree and duration of immunity to further infection are uncertain. As yet, no specific data in respect of diabetes are available. Will the immune response to infection be different with diabetes? So many questions are at present waiting to be addressed. With diabetes itself being a potential composite comorbidity, to what extent is outcome determined by additional renal and cardiovascular considerations? How have differing levels of glycaemic control and medication influenced outcome? Were drugs such as metformin and SGLT2 inhibitors discontinued on hospitalisation as advised and, if so, with what consequence? What proportion of patients needed immediate conversion to insulin? Did statins improve the anti-inflammatory response or, like non-steroidals, possibly the reverse? Did ACE2 inhibitors adversely affect outcome or not? The answers will be awaited with considerable interest. Meanwhile, as the pandemic takes its course, the focus moves towards an exit strategy from current restrictions, so far untested and almost impossible to configure without risking infection for those as yet unaffected by illness. By having taken extra precaution with those most vulnerable including diabetes, these individuals remain at risk, requiring a level of continued care probably until a safe and effective vaccine becomes available. Suggestions have been mooted of a differential phased release, but there is no easy answer, and much will be learnt from the experience. This pandemic will eventually settle, but it is unlikely to be the last. Knowledge gained should be used to prepare well in advance for such future contingency and, as ever, the extra burden of diabetes in the event of overwhelming contagious disease must be constantly addressed. Infection and Diabetes Impaired leukocyte function in patients with poorly controlled diabetes Commentary: COVID-19 in patients with diabetes Coronavirus and diabetes: an update Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centred, retrospective, observational study Clinical characteristics of coronavirus disease 2019 in China Characteristics of and public health responses to the coronavirus disease 2019 outbreak in China Diabetes is a risk factor for the progression and prognosis of COVID-19 Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med Prevalence and impact of diabetes among people infected with SARS-CoV-2 Preliminary estimates of the prevalence of selected underlying health conditions among patients with coronavirus disease 2019 -United States Deaths involving COVID-19, England and Wales Clinical characteristics of Covid-19 in New York City Pandemic influenza -surge capacity and prioritisation. Final Guidance Preparations for pandemic influenza (diabetes) Effectiveness of influenza vaccine in reducing hospital admission in people with diabetes Our response to Covid-19 as endocrinologists and diabetologists Clinical considerations for patients with diabetes in times of COVID-19 epidemic Publications approval reference 001559. NHS England, Royal College of Physicians, and the Association of British Clinical Diabetologists Letter to Health Care Professionals from the National Diabetes Inpatient COVID Response Team Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study 


id: cord-028967-l5ioyhur
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   key: cord-028967-l5ioyhur authors: Scherbaum, Werner A. title: Diabetes Update 2020: das Wichtigste für die ärztliche Praxis date: 2020-07-10 journal: Diabetologe DOI: 10.1007/s11428-020-00642-7 sha: doc_id: 28967 cord_uid: l5ioyhur At the virtual event Diabetes Update 2020, numerous new findings and recommendations on diagnosis, therapy and management of diabetes and related topics were presented, of which the topics type 2 diabetes, diabetes and heart, diabetes and pregnancy as well as vaccinations are described in detail in separate articles in the current issue of Der Diabetologe. In the following, the most important and, from the author’s point of view, most relevant news from the other diabetes-related subject areas are briefly presented. In der DIRECT-Studie wurde bei insgesamt 306 Patienten/Innen mit Typ-2-Diabetes in 49 hausärztlichen Praxen in Nordengland und Schottland geprüft, inwieweit durch ein Gewichtsmanagementprogramm eine starke Gewichtsreduktion und eine Diabetesremission erreicht werden können. Teilnehmer/ Innen der Interventionsgruppe erhielten u. a. einen Mahlzeitenersatz durch eine flüssige Formuladiät von 825-853 kcal pro Tag über 3-5 Monate; danach wurde stufenweise wieder eine Normalkost eingeführt. Die Kontrollgruppe wurde mit einer leitlinienorientierten Standardtherapie versorgt. In der Interventionsgruppe wurden die antidiabetische und die antihypertensive Therapie schon zu Studienbeginn abgesetzt. Nach 12 Monaten hatten 24 % der Teilnehmer/Innen der Interventionsgruppe, aber keiner in der Kontrollgruppe eine Gewichtsabnahme von mindestens 15 kg erreicht. Eine Diabetesremission (definiert durch einen HbA1c-Wert von weniger als 6,5 %) wurde bei 46 % der Teilnehmer/Innen der Interventionsgruppe, aber nur 4 % der Kontrollgruppe erzielt. Die 2019 publizierten 2-Jahres-Ergebnisse der Studie ergaben nun, dass eine Remission des Diabetes immer noch bei mehr als 1/3 der Teilnehmer/Innen der Interventionsgruppe, aber nur bei 3 % der Kontrollgruppe vorlag. Erwartungsgemäß war die Chance für eine Diabetesremission umso höher, je stärker die Gewichtsreduktion ausgeprägt war. Über die Reduktion der täglich zugeführten Kalorien hinaus spielt die Zusammensetzung der Mahlzeiten für den Erfolg einer Gewichtsverminderung bei Adipositas und T2D eine wesentliche Rolle. Das zeigte auch eine kürzlich publizierte dänische Studie, bei der Personen mit Typ-2-Diabetes über 6 Wochen hinweg entweder mit einer kohlenhydratarmen Diät mit 30 % Kohlenhydraten und einer entsprechenden Erhöhung des Fettgehalts auf 40 % oder einer isokalorischen Kost mit 50 % Kohlenhydraten und 33 % Fett ernährt worden waren und danach über 6 Wochen hinweg die andere Kost zuführten. Im Vergleich zu der Gruppe mit konventioneller Ernährung kam es in der Gruppe mit kohlenhydratarmer Diät zu einem signifikant stärkeren Abfall des HbA1c-Werts und der Nüchternglukosekonzen-tration sowie auch des postprandialen Glukoseanstiegs, des Leber-und des Pankreasfettgehalts [2]. Im Gegensatz zu den klassischen Ernährungsempfehlungen für Patienten/Innen mit Typ-2-Diabetes von 6 Mahlzeiten pro Tag ergab eine neue Studie, dass Menschen mit T2D von einer Beschränkung auf 3 Mahlzeiten pro Tag profitieren. Die Zufuhr von 3 Mahlzeiten pro Tag führte im Vergleich zu einer isokalorischen Zufuhr von 6 Mahlzeiten pro Tag . Dies ist eine ausge-sprochen positive Entwicklung. In einer weiteren Arbeit der DPV-Initiative wurde gezeigt, dass bei insgesamt 3553 Patienten/Innen mit T1D, jünger als 18 Jahre (medianes Alter: 12 Jahre), mit einer Diabetesdauer von mehr als 1 Jahr (im Mittel: 4,2 Jahre), die HbA1c-Werte in den ersten 12 Monaten nach Beginn der CGM im Vergleich zu den Ausgangswerten hochsignifikant niedriger waren und dass die Häufigkeit der diabetischen Ketoazidose unter Anwendung der CGM binnen 6-12 Monaten signifikant abnahm [11] . Schließlich wurde in einer Zusammenarbeit der deutsch/österreichischen DPV-Gruppe und einem australischen Konsortium (WACDD) nachgewiesen, dass bei Kindern mit einer Manifestation des T1D vor dem 15. Lebensjahr (Daten von 1995-2016) der mittlere HbA1c von 8,3 auf 7,8 % (DPV) bzw. von 9,2 auf 8,3 % (WACDD) reduziert wurde und gleichzeitig die Rate an schweren Hypoglykämien jährlich um 2 % (DPV) bzw. 6 % (WACDD) abnahm ([12]; . Abb. 2). Dies zeigt, dass -im Gegensatz zu der altbekannten Botschaft aus der DCCT -bei einer strukturierten Diabetestherapie mit Anwendung der neuen Technologien ein besserer HBA1c-Zielwert bei T1D nicht generell mit einer Erhöhung des Hypoglykämierisikos einhergeht. Die Alltagstauglichkeit eines modernen Closed-Loop-Systems wurde in einer multizentrischen Studie aus den USA belegt, in der 168 Patienten/Innen mit T1D (Alter: 14-71 Jahre, HbA1c: 5,4-10,6 %) randomisiert entweder mit einem Closed-Loop-System oder mit einer sensorunterstützten Pumpentherapie über 6 Monate hinweg behandelt wurden. Mit dem Closed-Loop-System stieg die Zeit im Zielbereich von 70-180 mg/dl (3,9-10 mmol/l) von 61 % auf 71 %, während sie in der Kontrollgruppe unverändert bei 59 % blieb. Auch bezüglich der mittleren Glukosekonzentration und des HbA1c-Wertes fand sich ein deutlicher Vorteil des Closed-Loop-Systems. Episoden von schweren Hypoglykämien traten mit beiden Systemen nicht auf [13] . Das Die Ergebnisse neuer Studien bestärkten den Erfolg intravitrealer Anti-VEGF-Injektionen, insbesondere bei der proliferativen diabetischen Retinopathie. Hervorzuheben ist dabei ein Therapieschema nach dem sog. Protokoll S, bei dem erstmals 2015 in einer randomisierten Studie bei Patienten/Innen mit PDR der Vorteil einer kontinuierlichen repetitiven Therapie mit dem Anti-VEGF Ranibizumab gegenüber einer panretinalen Lasertherapie (2-3 Sitzungen mit ca. 1500 Herden) nachgewiesen wurde. In einem Follow-up von 2 Jahren verbesserte sich der Visus in der mit Anti-VEGF behandelten Gruppe im Vergleich zur Gruppe mit Lasertherapie signifikant, und auch die Rate der erforderlichen Vitrektomien war in ersterer Gruppe niedriger [14] . Der Vorteil des Algorithmus von Protokoll S wurde auch in einer aktuellen Posthoc-Studie bestätigt, wobei es unter einer solchen Therapie nach 6 Monaten in 56 % der Fälle zu einer Auflösung der Neovaskularisationen kam. Die Autoren/ Innen folgerten aus den Ergebnissen dieser Studie, dass unter der IVOM-Therapie mit weniger DME, höherem Visus und dauerhaft besserem Gesichtsfeld zu rechnen sei [15] . Ähnlich positive Ergebnisse Hypertonie · Diät, Essen und Ernährung · Adipositas · Diabetische Angiopathien · Migranten/Innen Diabetes update 2020: the most important points for medical practice Abstract At the virtual event Diabetes Update 2020, numerous new findings and recommendations on diagnosis, therapy and management of diabetes and related topics were presented, of which the topics type 2 diabetes, diabetes and heart, diabetes and pregnancy as well as vaccinations are described in detail in separate articles in the current issue of Der Diabetologe. In the following, the most important and, from the author's point of view, most relevant news from the other diabetes-related subject areas are briefly presented. Hypertension · Diet, food, and nutrition · Obesity · Diabetic angiopathies · Migrants Abb. 1 9 Reduktion der Knochendichte (BMD ["bone mineral density"]) 1 Jahr nach bariatrischen Operationen, mRYBG Roux-en-Y-Magenbypass ("Roux en Y gastric bypass"), GCP , operative Faltenbildung der großen Kurvatur mit Fixierung der Falte ohne Resektion von Gewebe (["greater curvature plication"], Modifikation der SG), SG Schlauchmagenanlage ("sleeve gastrectomy"). (Aus [7]) gegenüber einer panretinalen Lasertherapie ergaben sich in einer randomisierten kontrollierten Phase-2b-Studie mit dem Anti-VEGF Aflibercept, in welcher ebenfalls eine Regression der Neovaskularisation nachgewiesen wurde [16] . Abb. 3 9 Behandlung eines chronischen diabetischen Fußulkus mit topisch verabreichtem hyperbarem Sauerstoff [26] . Mit freundlicher Genehmigung von Advanced Oxygen Therapy, Inc. Knies gingen stark zurück [21] . In einer Studie aus dem Südwesten Englands wurde gefunden, dass die Inzidenz diabetesbedingter Majoramputationen der unteren Extremität signifikant invers mit der Bereitstellung von Fußbehandlungseinrichtungen korreliert ist und die Einführungen einer entsprechenden Infrastruktur innerhalb von 2 Jahren zu einer signifikanten Reduktion der Majoramputationen führte [22] . Im internationalen Vergleich sind die Amputationsraten der unteren Extremitäten in Deutschland hoch. In einer kürzlich publizierten populationsbasierten Beobachtungsstudie wurden die kompletten nationalen Krankenhausentlassungsdaten von 2005-2015 anhand der DRG-Einträge ausgewertet. Dabei ergab sich eine Reduktion der Zahl der Amputationen an den unteren Extremitäten, insbesondere von Majoramputa-tionen oberhalb des Knies, in diesem Zeitraum, die bei Frauen (-25 %) deutlich stärker ausgeprägt war als bei Männern (-2,6 %). Die Krankenhaussterblichkeit aller Fälle mit Amputationen an den unteren Extremitäten sank von 11,2 % im Jahr 2005 auf 7,7 % in 2017 [23] . Dies weist auf eine Verbesserung der Versorgung von Patienten/Innen mit einem diabetischen Fußsyndrom hin. Dennoch liegt die absolute Zahl an Amputationen in Deutschland deutlich höher als in anderen vergleichbaren Ländern wie den Niederlanden oder in England. Entsprechend einer internationalen Vergleichsstudie zu Amputationen im Jahr 2015 liegt Deutschland mit 9,2 Majoramputationen pro 100.000 Personen/ Jahr im höchsten Viertel; der OECD-Durchschnitt beläuft sich auf 6,4 Majoramputationen pro 100.000 Einwohner/ Jahr [24] . Die Ergebnisse einer kürzlich publizierten Studie fachten die Diskussion um den Stellenwert der hyperbaren Sauerstofftherapie zur Förderung der Abheilung diabetischer Fußgeschwüre neu an. In der randomisierten doppelblinden plazebokontrollierten (durch Scheinanwendung) Studie wurde die Effektivität einer häuslichen, zyklischen, topischen Sauerstoffdrucktherapie zur Behandlung von therapierefraktären diabetischen Fußulzera untersucht, die unter einer alleinigen Standardtherapie nicht zur Abheilung gebracht werden konnten. Die Ergebnisse waren ausgesprochen positiv: Nach 12 Wochen wurde unter der TWO2-Therapie in 42% der Betroffenen eine komplette Ulkusheilung erreicht; in der Kontrollgruppe waren es nur 14 %. In der mit TWO2 behandelten Gruppe waren 12 Monate nach Beginn der Studie 56 % der Ulzera abgeheilt, in der Kontrollgruppe 27 % ( [26] , . Abb. 3). Der Referent wies darauf hin, dass die Ergebnisse dieser Studie im Gegensatz zu bisher publizierten Untersuchungen stehen, in welchen kein Vorteil einer lokal applizierten Sauerstofftherapie festgestellt worden war. Er verwies aber auf den Beschluss des G-BA, nach dem diabetische Fußulzera ab Wagner-Stadi-um 2 unter bestimmten Bedingungen mit HBO behandelt werden dürfen (s. unten). Die Vorgaben des G-BA zum möglichen Einsatz der HBO setzen eine leitliniengerechte Therapie in einer für den diabetischen Fuß qualifizierten Einrichtung und Erfolglosigkeit der Standardtherapie voraus. Der Referent betonte, dass es wesentlich kostengünstigere Behandlungen des schweren diabetischen Fußulkus gibt, deren positive Wirkung in mehreren gut kontrollierten Studien eindeutig nachgewiesen wurde, wie z. B. den Einsatz des "total contact cast", der jedoch in Deutschland finanziell nicht vergütet wird. Six-month randomized, multicenter trial of closedloop control in type 1 diabetes Panretinal photocoagulation vs intravitreous ranibizumab for proliferative diabetic retinopathy. A randomized clinical trial Rationale and application of the protocol S antivascular endothelial growth factor algorithm for proliferative diabetic retinopathy Clinical efficacy of intravitreal Aflibercept versus panretinal photocoagulation for best corrected visual acuity in patients with proliferative diabetic retinopathy at 52 weeks (CLARITY): a multicentre, single-blinded, randomised, controlled, phase 2b, non-inferiority trial Association between vessel density and visual acuity in patients with diabetic retinopathy and poorly controlled type 1 diabetes Optical coherence tomography angiography versus fluorescein angiography in the diagnosis of ischaemicdiabeticmaculopathy Detection of clinically unsuspected retinal neovascularization with wide-field optical coherence tomography angiography A lack of decline in major nontraumatic amputations in Texas: contemporary trends, risk factor associations, and impact of revascularization Decreasing rates of major lower-extremity amputation in people with diabetes but not in those without: a nationwide study in Belgium Diabetes-relatedmajorlimbamputationincidence is strongly related to diabetic foot service provision and improves with enhancement of services: peer review of the South-West of England Amputation rates of the lower limb by amputation level-observationalstudyusingGermannational hospital discharge data from Lowerextremityamputationratesinpeople with diabetes as an indicator of health systems performance. A critical appraisal of data collection 2000-2011 by the Organization for Economic Cooperation and Development (OECD) Impact of severe diabetic kidney disease on the clinical outcome of autologous cell therapy in people with diabetes and critical limb ischaemia A multinational, multicenter, randomized, doubleblinded, placebo-controlled trial to evaluate the efficacy of cyclical topical wound oxygen therapy (TWO2) in the management of chronic diabetic foot ulcers: The TWO2 Study Beschluß des Gemeinsamen Bundesausschusses über eine Änderung der Richtlinie Methoden vertragsärztlicher Versorgung. Hyperbare Sauerstofftherapie bei diabetischem Fußsyndrom. Beschlußdatum: 21.09.2017 Cardiovascular events and mortality in white coat hypertension: a systematic review and metaanalysis Nondipping nocturnal blood pressure predicts sleep apnea in patients with hypertension Bedtime hypertension treatment improves cardiovascular risk reduction: the hygia chronotherapytrial Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? COVID-19 and the cardiovascular system Renin-Angiotensin-Aldosterone System inhibitors in patients with Covid-19 Cardiovascular disease, drug therapy, and mortality in Covid-19 Renin-angiotensin-aldosterone system blockers and the risk of Covid-19 Renin-angiotensin-aldosteronesysteminhibitors and risk of Covid-19 Prevalence of comorbidities and its effects in coronavirus disease 2019 patients: a systematic review and metaanalysis Diabetes and Ramadan: practical guidelines Fallstricke in der Diabetesdiagnostik: wird zu lax mit den Laborwerten umgegangen Preventing misdiagnosis of diabetes in the elderly: age-dependent HbA1c reference intervals derived from two population-based study cohorts Progressinautomated urinalysis "Severe acute respiratory syndrome coronavirus 2" SGLT Natriumabhängiger Glukosekotransporter ("sodium dependent glucose transporter") Typ-1-Diabetes Typ-2-Diabetes Topische Sauerstoffdrucktherapie ("topical wound oxygen") Vaskulärer endothelialer Wachstumsfaktor ("vascular endothelial growth factor") Decreasing trends in mean HbA1c are not associated with increasing rates of severe hypoglycemia in children: a longitudinal analysis of two contemporary population-based pediatric type 1 diabetes registries from Australia, and Germany/ Austria between 1995 and 2016. Diabetes Care 


id: cord-030631-cc79j9j4
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   key: cord-030631-cc79j9j4 authors: Marcus, Benjamin A.; Achenbach, Peter; Ziegler, Anette-Gabriele title: Typ-1-Diabetes: Früherkennung und Ansätze zur Prävention: Update 2020 date: 2020-08-19 journal: Diabetologe DOI: 10.1007/s11428-020-00668-x sha: doc_id: 30631 cord_uid: cc79j9j4 The incidence of type 1 diabetes is increasing, especially in young children. Early diagnosis is possible in the asymptomatic stage of islet autoimmunity. Screening is offered to high-risk families, but also feasible and useful in the general population, in studies such as Fr1da(plus) in Bavaria (Germany). Complications at clinical manifestation can be prevented by early diagnosis. Participation in experimental interventions to delay stage progression is possible. Numerous approaches to secondary prevention are being pursued. Treatment with the monoclonal antibody teplizumab successfully delayed progression to clinical diabetes in patients in stage 2. Infants at high risk for developing type 1 diabetes can be identified by genetic screening. Primary prevention pursues, among others, the goal of preventing the onset of the autoimmune reaction. The POInT trial aims to improve immune tolerance to insulin by oral exposure in high-risk children and to delay or prevent the onset of autoimmunity. Following up on the focus issue “Early detection and preventive treatment of type 1 diabetes” published in this journal in 2018, this article gives an update on selected developments over the past 2 years. Große prospektive Geburtskohorten haben unser Verständnis für die Entstehung des Typ-1-Diabetes und den natürlichen Verlauf dieser chronischen Autoimmunerkrankung entscheidend vorangebracht, und tun dies ist auch weiterhin. Wir kennen die genetischen Faktoren, die das Auftreten der Erkrankung begünstigen. Wir können einen Typ-1-Diabetes heute durch den Nachweis von Inselantikörpern diagnostizieren, lange bevor es zu Veränderungen des Glukosestoffwechsels oder gar zu Symptomen kommt. In einer bahnbrechenden Präventionsstudie konnten die klinische Manifestation bereits um mehrere Jahre hinausgezögert und die Betazellfunktion stabilisiert werden, was auch die Suche nach ei-ner kausalen Therapie befruchten könnte. Das immer bessere Verständnis der komplexen Vorgänge, die zur Fehlleitung des Immunsystems und zur fortschreitenden Zerstörung von Betazellen führen, eröffnet darüber hinaus verschiedene Ansatzpunkte, das Entstehen von Autoimmunität zu verhindern und den Prozess aufzuhalten. Im Themenheft dieser Zeitschrift Früherkennung und präventive Behandlung des Typ-1-Diabetes -Weichenstellungen für die Zukunft [1] vom Juni 2018 wurden diese Bereiche bereits ausführlich dargestellt. In diesem Beitrag sollen als Update ausgewählte neue Ergebnisse und Entwicklungen der letzten 2 Jahre vorgestellt werden. Der Nachweis von gegen unterschiedliche Betazellantigene gerichteten Autoantikörpern im Blut ist der etablierte und derzeit wichtigste Marker für den Autoimmunprozess, der den Typ-1-Diabetes charakterisiert. Es kommt zu einem Untergang der insulinproduzierenden Zellen der Bauchspeicheldrüse durch autoreaktive T-Zellen mit zunächst langsam, dann kurz vor der Manifestation rasch abnehmender Insulinproduktion. Eine gestörte Glukosetoleranz lässt sich erst feststellen, wenn bereits ein Großteil der Betazellen ihrer Funktion nicht mehr nachkommen kann. Die 4 wesentlichen Autoantikörper sind Insulinautoantikörper (IAA), Glutamatdekarboxylaseautoantikörper (GADA), Antikörper ge-gen das insulinomassoziierte Antigen 2 (IA-2A) und Zinktransporter-8-Autoantikörper (ZnT8A). Autoantikörpern markiert das Frühstadium des Typ-1-Diabetes Der Nachweis von 2 oder mehr dieser Autoantikörper beim asymptomatischen Kind ohne gestörten Glukosestoffwechsel ist inzwischen als eines der Frühstadien des Typ-1-Diabetes (Stadium 1) anerkannt. Beim Stadium 2 liegen zudem mäßig erhöhte Nüchternglukosewerte und/oder eine gestörte Glukosetoleranz vor. Der (neu) manifestierte Typ-1-Diabetes nach gültigen klinischen und laborchemischen Kriterien ist das Stadium 3 (. Tab. 1). Anhand In der COVID-19-Pandemie leistet die Fr1da plus -Studie einen über die Typ-1-Diabetes-Früherkennung hinausgehenden Beitrag zur epidemiologischen Forschung. Mit einem von italienischen Wissenschaftlern entwickelten, nichtkommerziellen Verfahren werden die Kapillarblutproben auch auf IgG-Antikörper (IgG: Immunglobulin G) gegen die Rezeptorbindungsdomäne des S-Proteins von SARS-CoV-2 ("severe acute respiratory syndrome coronavirus 2") untersucht. Der Luciferaseimmunopräzipitationstest (LIPS) funktioniert nach einem ähnlichen Prinzip wie der Nachweis von IAA [19] . Dabei wird auch auf anonymisierte Fr1da-Proben seit August 2019 zurückgegriffen. So kann die Immunitätslage von Kindern im stark betroffenen Bayern vor und im gesamten Verlauf der Pandemie ermittelt werden [13] . The incidence of type 1 diabetes is increasing, especially in young children. Early diagnosis is possible in the asymptomatic stage of islet autoimmunity. Screening is offered to highrisk families, but also feasible and useful in the general population, in studies such as Fr1da plus in Bavaria (Germany). Complications at clinical manifestation can be prevented by early diagnosis. Participation in experimental interventions to delay stage progression is possible. Numerous approaches to secondary prevention are being pursued. Treatment with the monoclonal antibody teplizumab successfully delayed progression to clinical diabetes in patients in stage 2. Infants at high risk for developing type 1 diabetes can be identified by genetic screening. Primary prevention pursues, among others, the goal of preventing the onset of the autoimmune reaction. The POInT trial aims to improve immune tolerance to insulin by oral exposure in high-risk children and to delay or prevent the onset of autoimmunity. Following up on the focus issue "Early detection and preventive treatment of type 1 diabetes" published in this journal in 2018, this article gives an update on selected developments over the past 2 years. Um zu prüfen, ob Teplizumab die klinische Manifestation verhindern kann, wurden in einer TrialNet-Studie Angehörige von Personen mit Typ-1-Diabetes behandelt, die selbst bereits ein Frühstadium mit multiplen Inselautoantikörpern und eine Dysglykämie oder gestörte Glukosetoleranz (Stadium 2) entwickelt hatten. Die Ergebnisse dieser Untersuchung, die für mehr als die Hälfte der Behandelten eine Verdoppelung der Zeit bis zur klinischen Erkrankung auf 4 Jahre ergaben, wurden im New England Journal of Medicine (NEJM) publiziert [14] . Somit konnte erstmals die Manifestation der Erkrankung wirksam hinausgezögert werden, was einen Durchbruch für die präventive Therapie des Typ-1-Diabetes darstellt. In die doppelblinde, randomisierte und plazebokontrollierte Phase-2-Studie wurden 76 Verwandte von Patienten mit Typ-1-Diabetes, 2 oder mehr Autoantikörpern und Dysglykämie eingeschlossen, mehrheitlich Kinder ab 8 Jahren und Jugendliche. Sie erhielten 2 Wochen lang 1-mal täglich Infusionen mit Teplizumab oder Kochsalz. Im Followup erfolgten mindestens halbjährlich Glukosetoleranztests, die Nachbeobachtungszeit betrug im Median etwas über 2 Jahre, 75 % der Probanden konnten über mehr als 3 Jahre nachverfolgt werden. Bei 19 (43%) der 44 mit Teplizumab behandelten Teilnehmenden und 23 (72 %) von 32 in der Plazebogruppe wurde ein klinischer Typ-1-Diabetes diagnostiziert. Im ersten Jahr nach der Behandlung war der Effekt besonders ausgeprägt: Hier manifestierte sich die Erkrankung nur bei 3 (7 %) Teilneh-mern in der Teplizumab-vs. 14 (44 %) in der Plazebogruppe. Jährlich erkrankten 14,9 % Auf den diesjährigen "Scientific Sessions" der "American Diabetes Association" (ADA) wurden Daten aus dem erweiterten Follow-up der Studie vorgestellt -und bei der medianen Hinauszögerung noch ein weiteres, 3., Jahr hinzugefügt. Zudem war Teplizumab in der Lage, den C-Peptid-Abfall nach Manifestation nicht nur zu bremsen, sondern signifikant umzukehren. Dies könnte bedeuten, dass nicht nur die Zerstörung der Betazellen gestoppt, sondern auch die Insulinproduktion in dysfunktionalen Zellen teilweise wiederhergestellt wurde [26] . Auch wenn derzeit noch "nur" davon ausgegangen werden sollte, dass sich für die behandelten Patienten der Beginn der Erkrankung weiter in die Zukunft verschiebt und der Effekt bei einer dauerhaft therapiebedürftigen Erkrankung moderat erscheinen mag, wirkt sich gerade bei Kindern jedes gewonnene klinisch gesunde Jahr noch weit mehr aus als im Erwachsenenalter. Für eine individualisierte Sekundärprävention interessant wird die Tatsache, dass anhand von Biomarkern -HLA-Merkmalen (HLA: humanes Leukozytenantigen) und dem Fehlen von ZnT8A -abgeschätzt werden kann, bei welchen Patienten ein Ansprechen auf die Anti-CD3-Behandlung bessere Erfolgschancen hat [28] . Inzwischen wurden mehr als 60 Genloci identifiziert, die in unterschiedlichem Ausmaß für das Entstehen eines Typ-1-Diabetes prädisponieren. Die meisten davon sind mit der Immunantwort so-wie der Entwicklung und dem Erhalt von Toleranz gegenüber Antigenen assoziiert [4] . Die genetische Empfänglichkeitalleinführtaberwahrscheinlichnicht zum Entstehen der Inselautoimmunität. Es wird angenommen, dass Umweltfaktoren, die auf eine genetische Prädisposition treffen, entscheidend mit zur Initiierung des Autoimmunprozesses beitragen. Dabei liegt es nahe, dass dem frühen Säuglingsalter, in dem dieser Prozess noch nicht in Gang gekommen ist, eine besondere Bedeutung zukommt [23] . Nichtpharmakologische Interventionen zielen auf die Zusammensetzung der Ernährung und ggf. gezielte Supplementationen ab, auch das Darmmikrobiom rückt immer mehr in den Fokus [33] . In der interventionellen Präventionsstudie BABYDIET wurde gezeigt , dass -obwohl die zu frühe Einführung von Gluten mit der Beikost, vor dem 3. Lebensmonat, mit einem höheren Risiko einhergeht -eine darüber hinausgehende glutenfreie Ernährung das Entstehen der Inselautoimmunität nicht verhindert. Auch durch Elimination anderer potenziell antigener Proteine durch die Verwendung stark hydrolysierter Säuglingsmilch konnte in der prospektiven TRIGR-Studie die Diabetesinzidenz nicht gesenkt werden [16, 18] . Es lassen sich weiterhin keine über die allgemeingültigen Empfehlungen zu einer gesunden Säuglingsernährung hinausgehenden Ernährungsmaßnahmen zur Senkung des Typ-1-Diabetes-Risikos ableiten. Die Identifikation von Neugeborenen und Säuglingen mit einem hohen genetischen Typ-1-Diabetes-Risiko ist heute einfach und kostengünstig möglich, sodass sie auch in bevölkerungsweiten Studien angeboten werden kann. Die "Global Platform for the Prevention of Autoimmune Diabetes" (GPPAD), ein Netzwerk kooperierender Wissenschaftler und Institutionen [37] , führt dies seit 2017 regional in 5 europäischen Ländern durch. In Deutschland wird das Virusinfekte werden mit dem Typ-1-Diabetes in Verbindung gebracht, insbesondere virale Atemwegsinfekte in der frühen Kindheit und Infektionen mit Enteroviren und Durchfallerregern. Hier könnten zukünftig entsprechende Impfungen, z. B. gegen Coxsackie-Viren [31] , oder antivirale Therapien zur Senkung des Erkrankungsrisikos beitragen [10] . Dervorfast15 Jahreneingeführten Rotavirenimpfung wird ein kürzlich festgestellter geringer Rückgang der Diabetesinzidenz bei vollständig geimpften Kindern zugeschrieben. Hinweise hierzu lieferten retrospektive Auswertungen aus Australien und den USA [24, 27] , wobei die Ergebnisse einer weiteren amerikanischen Analyse dies zuletzt wieder in Frage stellten [11] . Zumindest lässt sich sicher sagen, dass auch die Rotavirenimpfungso wie alle anderen empfohlenen Schutzimpfungen -sich keinesfalls negativ auf das Typ-1-Diabetes-Risiko auswirkt. Die erstmalige, wirksame Verzögerung der Manifestation mit Teplizumab allein ist schon bemerkenswert [32] , die mögliche Reaktivierung zuvor nicht sezernierender Betazellen könnte auch die Entwicklung kausaler Therapien mit vorantreiben. In größeren Studien mit mehreren Behandlungszyklen und in der weite-ren langfristigen Nachbeobachtung der Studienpatienten wird das Potenzial der Substanz weiter untersucht werden. Die Kombination mit anderen, schon im frühen Stadium 3 in klinischen Studien eingesetzten, vielversprechenden und verträglichen Immunmodulatoren wie z. B. Abatacept oder niedrig dosiertem Antithymozytenglobulin, die an anderen Stellen der Pathogenese des Typ-1-Diabetes angreifen [5, 9] , sowie mit weiteren aufkommenden betazellregenerativen Therapien wird bereits geplant. Studien zur Früherkennung stoßen bei Eltern auf Zuspruch, und auch Familien, die bisher nicht von Typ-1-Diabetes betroffen waren, sind am Angebot primärer und sekundärer Präventionsstudien sehr interessiert. Die Möglichkeit, Komplikationen bei der Manifestation zu verhindern und erste Erfolge in der medikamentösen Sekundärprävention werden die schon länger geführte Debatte um eine Verstetigung und Ausweitung von Typ-1-Diabetes-Früherkennungsuntersuchungen, z. B. als zusätzliches Angebot bei den gesetzlichen Vorsorgeuntersuchungen, sicher befruchten [22] . Früherkennung und präventive Behandlung des Typ-1-Diabetes Typ-1-Diabetes im asymptomatischen Frühstadium Classification and diagnosis of diabetes: standards of medical care in diabetes-2020 Type 1 diabetes The challenge of modulating β-cell autoimmunity in type 1 diabetes Type 1 diabetes trialnet: a multifaceted approach to bringing disease-modifying therapy to clinical use in type 1 diabetes Predicting type 1 diabetes using biomarkers Birth and coming of age of islet autoantibodies A future for CD3 antibodies in immunotherapy of type 1 diabetes Rationale for enteroviral vaccination and antiviral therapies in human type 1 diabetes Association betweenRotavirusvaccinationandtype1diabetes in children Teplizumab preserves C-peptide in recent-onset type 1 diabetes: two-year results from the randomized, placebo-controlled Protégé trial Etablierte Früherkennungsstudie zu Typ-1-Diabetes testet nun Tausende Kinder auch auf Antikörper gegen SARS-CoV-2 An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes Landmark models to define the age-adjusted risk of developing stage 1 type 1 diabetes across childhood and adolescence Prevention strategies for type 1 diabetes: a story of promising efforts and unmet expectations Recruiting young pre-symptomatic children for a clinical trial in type 1 diabetes: Insights from the Fr1da insulin intervention study Effect of hydrolyzed infant formula vs conventional formula on risk of type 1 diabetes: the TRIGR randomized clinical trial Ketoacidosis at onset of type 1 diabetes in children up to 14 years of age and the changes over a period of 18 years in Saxony, Eastern-Germany: A population based register study Immunological biomarkers for the development and progression of type 1 diabetes Screening for type 1 diabetes: are we nearly there yet? Type 1 diabetes-early life origins and changing epidemiology Association of rotavirus vaccination with the incidence of type 1 diabetes in children Treatment of type 1 diabetes with teplizumab: clinical and immunological followup after 7 years from diagnosis Provention bio's teplizumab continued to significantly delay the onset of insulin-dependenttype1diabetes(T1D)inpresymptomatic patients Lower incidence rate of type 1 diabetes after receipt of the rotavirus vaccine in the United States Traveling down the long road to type 1 diabetes mellitus prevention Who is enrolling? The path to monitoring in type 1 diabetestrialnet'spathwaytoprevention Continuous glucose monitoring predicts progression to diabetes in autoantibody positive children A hexavalent coxsackievirus B vaccine is highly immunogenic and has a strong protective capacity in mice and nonhuman primates Delaying diabetes onset The human gut microbiome in early-onset type 1 diabetes from the TEDDY study Früherkennung des Typ-1-Diabetes in der Fr1da-Studie Identification of infants with increased type 1 diabetes genetic risk for enrollment into Primary Prevention Trials-GPPAD-02 study design and first results Why is the presence of autoantibodies against GAD associated with a relatively slow progression to clinical diabetes? Oral insulin therapy for primary prevention of type 1 diabetes in infants with high genetic risk: the GPPAD-POInT (global platform for the prevention of autoimmune diabetes primary oral insulin trial) study protocol Yield of a public health screening of children for islet autoantibodies in Bavaria 


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   key: cord-214006-0w6bqrox authors: Aghdam, Atae Rezaei; Watson, Jason; Miah, Shah J; Cliff, Cynthia title: Towards Empowering Diabetic Patients: A perspective on self-management in the context of a group-based education program date: 2020-10-26 journal: nan DOI: nan sha: doc_id: 214006 cord_uid: 0w6bqrox This paper provides a novel framework for maximizing the effectiveness of the Diabetes Group Education Program, which could be generalized in any similar problem context. Diabetes is recognised as the world's fastest-growing chronic disease (Australia 2020; Lovic et al. 2020) . According to the International Diabetes Federation (IDF), by 2040 one adult in ten will have diabetes (642 million) (Australia 2020 ). Diabetes is a chronic and progressive disease, which needs continuing self-management and self-awareness for a lifestyle change (Kjellsdotter et al. 2020) . Selfmanagement is one of the most key success factors impacting the progression of type-2 diabetes for patients, as the decisions that they make daily considerably impact their health outcomes (Funnell and Anderson 2004) . Patients play a pivotal role in their self-care as they are doing more than 95% of their diabetes care outside of medical centres or at home (Su et al. 2019) . OHCs as affordable and easily accessible 24/7 services, can facilitate self-management of diabetics by offering health-related advice and stories, social and emotional support (Aghdam et al. 2018 ). An OHC refers to a group of people who interact with each other in an online platform about similar health issues (Wang et al. 2017) . Due to the fact that people tend to trust others who are in a similar situation rather than organisations, businesses, or government figures and media, it stands to reason that the content shared by peers in OHCs has potential to encourage community members to engage in health-related online activities (Irshad et al. 2013; Litchman and Edelman 2019) . Participating in OHCs progressively transforms patients from passive recipients of healthcare services to active agents (Bragazzi 2013) . As active agents, patients can access, share and integrate their resources, sharing their experiences and stories, and emotionally supporting peers to achieve their health-related goals (Forouzandeh and Aghdam 2019) (Aghdam et al. 2020) . The empowerment of patients improves the patients' role in co-creation, co-designing, and co-delivering health services (Ciasullo et al. 2017) . This is essentially a reality for people with chronic disease such as diabetes patients who need informational and emotional supports that allow them to be successful in their disease self-management (Litchman and Edelman 2019) . In this regard, the diabetes education program has been a focus of prior research as a specific intervention that supports diabetes self-management (Findlay-White et al. 2020) . OHCs provide opportunities for members to exchange new ideas, knowledge and information about diabetes selfmanagement, functioning as a bridge among people with type-2 diabetes and healthcare professionals and providing online discussion platforms to brainstorm potential solutions (Sim et al. 2008) . As such, this study aims to investigate the potential practices of online diabetes communities to address the following question; how can an online diabetes community empower patients in context of a Diabetes Group Education Program (DGEP)? The remainder of this paper is organised as follows; the next section describes the background of the literature. The following section explains the research methodology followed by the trustworthiness process. The discussion section provides a comprehensive overview of the contributions of the study from both theoretical and practical perspectives and the final section synthesises the findings and provides avenues for future research. Chronic disease is generally of long duration, slow progression, and impacts the quality of life (Martz et al. 2007 ). The care for people with chronic diseases such as type-2 diabetes is often complex and requires self-management as an essential element of the chronic care model (Wagner et al. 2001 ). Self-management includes actions and behaviours to manage the psychical, emotional, and social effects of the chronic disease (Adams et al. 2004 ). One of the key methods for self-management of chronic disease and improved health outcomes is patient education (Ellis et al. 2004; Mensing and Norris 2003) . Patient education is the keystone of chronic disease self-management and is significant in achieving positive health outcomes for chronic disease patients (Ellis et al. 2004; Mensing and Norris 2003) . Patients need support, education, guidance and empowerment from their healthcare providers to tackle barriers to effective self-management (Diabetes 2009 ). Studies contended that participation in self-management courses also improves patient confidence, self-management skills and ability to self-manage their chronic disease, and improves the quality of life (Turner et al. 2015) . Diabetes group education programs typically assist patients to achieve knowledge and skills and confidence to manage their diabetes as well as opportunities to interact with peers and healthcare providers (Jonkman et al. 2016) . Group interactions facilitate further learning and raise motivation by interacting and learning from the experience of others (Odgers-Jewell et al. 2017) . Research shows that diabetes group-based education programs benefit patients who derive social and emotional support from discussion with others (Steinsbekk et al. 2012 ). This type of active participation by Australasian Conference on Information Systems Aghdam & Watson 2020, Wellington Towards Empowering Diabetic Patients patients in their health journey leads to value co-creation (Osei-Frimpong et al. 2015) . In the healthcare context value co-creation refers to "activities centered around the individual patients or in collaboration with numbers of the service delivery network including the patient, family, friends, other patients, health professionals and the outside community" (McColl-Kennedy et al. 2012, p. 6) . Value is co-created synergistically and digital health platforms such as OHCs act as a coordinating device between community members (Smedlund 2016) . Thus, digital health platforms such as OHCs are ideal places for value co-creation (Aghdam et al. 2020; Kamalpour et al. 2020) . Because of the nature of the DGEP, patients face three different stages during their health journey; (1) prior to joining, (2) during the program, and (3) after the program. We adapted Customer-Dominant Logic (CDL) to divide the customer journey into these three phases. In fact, CDL argues that customers control the service situation and control is a relevant issue in many domains, and due to progressively empowered customers (Seybold 2001) , this direction will most likely continue in the future (Heinonen and Strandvik 2015) . Accordingly, in the healthcare domain, empowering patients in OHCs can activate value co-creation behaviour among stakeholders (Litchman et al. 2018 ). As diabetes self-management requires a patient-centred approach (Funnell et al. 2007) , in particular for a demand-driven decision making (e.g. in clinical settings -Miah, 2013) and to date, the most successful diabetes self-management group activities and classes have been evaluated based on empowerment theory (Heisler 2010) , our study applied empowerment theory in the context of OHCs and a diabetes group education program. Empowerment theory contends that actions, activities or structures might be empowering and the outcome of such process leads to being empowered (Zimmerman 2000) . According to empowerment theory, people need opportunities to become active in community decision-making to improve their quality of life. As such, we leverage an affordable and easily accessible 24/7 digital health platform such as OHCs to facilitate the process of selfmanagement through informational, social, and emotional support. The proposed framework goes beyond the existing system-centric approaches to a new mode of conceptualisation and practice, which focuses on interactions among all stakeholders in OHCs. The proposed framework addresses diabetesrelated needs and challenges including; informational, social, and psychological needs. In this study, we selected online Reddit diabetes communities as our data source. The interactions between users are mostly focused on the posts themselves and members will give the post all their attentions. There are numerous diabetes-related topics in this forum, which make it a promising source of users' interactions for this research study. Reddit is a social aggregation and public discussion website. In Reddit, three popular diabetes communities comprise of more than 60,000 members. In this study, we selected r/diabetes, r/type2diabetes, and r/diabetes_t2 communities. Within each community, there are a variety of threads and topics discussed by users. The total number of users in all of these communities was 59,400 in April 2020. From each topic, the tile and the content (e.g., textual information) were extracted without the additional information of the authors. A total of 189 topics were collected from Reddit from October 2019 to April 2020. In total 1989 threads were collected for analysis. Research argued that participation in diabetes group education program has multiple benefits for patients such as social and emotional support, and sharing experiences (Odgers-Jewell et al. 2017) . The Queensland University of Technology (QUT) offers a partnership face-to-face DGEP to patients who are newly diagnosed or living with the type-2 diabetes long term. Over the course of program, the QUT DGEP aims to provide a quality lifestyle intervention empowering type-2 diabetic patients to better manage their symptoms. The DGEP runs for 10 weeks and includes various types of activities such as; initial assessment, weekly one-hour personalized exercise session, one-hour interactive group education regarding diabetes-related topics (e.g., diet, mindfulness, foot care, living with a chronic condition, etc.), and a final assessment at the end of the program. The outcomes of this award-winning program are promising and all patients involved no longer needing to stay on the long waiting list of the hospitals. One of the most important objectives of the DGEP is to keep patients connected whilst outside the program. We, therefore, aim to extend the value of the face-to-face DGEP by identifying the potential practices on the online diabetes communities, proposing a diabetes OHC framework for keeping patients connected to the program after discharge from the program. Aghdam & Watson 2020, Wellington Towards Empowering Diabetic Patients We collected data from the three popular Reddit diabetes online communities (r/diabetes, r/type2diabetes, and r/diabetes_t2). Reddit is a popular forum for diabetes (Duggan and Smith 2013) . There are numerous health-related topics on this website, which make it a promising source of users' interactions for this research study. In addition, Reddit allows researchers to mine its data. Hence, we used the Python Reddit Application Programming Interface (API) Wrapper (PRAW) to collect the data. PRAW is a Python package that allows researchers to access, parse topics and subreddit, and extract the associated reply threads. As inclusion criteria for selecting posts and threads, we selected type-2 diabetes-related topics with more than 10 replies on each topic to obtain enough information. The interactions between users are mostly focused on the posts themselves and members will give the post all their attention. Demographic information about the participants was anonymized to guarantee the confidentiality and privacy of participants' data. In every stage of this research study, we followed the code of ethics for researchers of the Queensland University of Technology (QUT). The approval number is 1900001024. In this study, we conducted an inductive thematic analysis to identify emergent themes from the data. The six steps of thematic analysis provided by (Clarke et al. 2015) , guided us to identify the salient themes. Following the six steps of the thematic analysis and with the assistance of the NVivo 12 qualitative analysis software, we manually generated an initial list of codes. During the first step, we performed an initial analysis of the relevant topics and threads and recorded our notes via memo and annotation features of NVivo 12. In the second step, we inductively generated 106 nodes. In the third step, we combined codes revealing three overarching themes and nine subthemes. In the fourth step, which was reviewing and refining the themes, we reviewed all themes and subthemes to make sure that they followed a coherence pattern. During this phase, two themes were integrated because of their common content. In the fifth step, we concisely named the identified themes to reflect the story behind each theme and reflect what the themes are about. Hence, we named themes that address the research questions. Finally, in the sixth step, findings were synthesised to provide a concise and coherent report. In terms of testing the trustworthiness of the findings, we employed percent agreement as our method of inter-coder reliability checking. Two scholars, experienced in qualitative research and thematic analysis, checked different parts from creating initial codes to naming the themes. Each of them independently analysed the entire data and during the first meeting, the per cent agreement was 75% and after the second meeting, discussing the essence of the themes, a consensus was achieved and the overall results were 100%, making us confident about the reliability of our findings. After performing the thematic analysis, our analysis resulted in three emergent themes from the data. Themes include (1) exchange lifestyle-related advice, (2) experience of commonality, and (3) brainstorm potential solutions for daily challenges. Table 1 , summarises the thematic analysis outcomes. As evidenced in Table 1 , patient participation in diabetes online communities leads to the co-creation of value. For instance, in theme 1, patients shared resources such as articles, and videos with peers. Another key finding is to improve patients' psychological wellbeing by participating in online activities such as story sharing and encourage other members of the community in selfmonitoring. OHCs provide an opportunity for users to enhance their knowledge about symptoms, share their experience and advice. Information sharing by peers, experience and advice sharing, life-style related advice sharing, and sharing daily-basis activities are the most common activities identified by researchers in this study through thematically analysing the content of threads in the Reddit diabetes online communities. These types of giving and seeking (exchanging) advice are illustrative examples of value co-creation behaviours. In the value co-creation process, stakeholders such as organizations, patients or caregivers share, integrate and renew each other's resources ). Our analysis shows that diabetic users mostly shared their experience, stories, and online resources (e.g., research articles, YouTube videos, and websites' URLs). Resource exchange is a mutual action taken by stakeholders in OHCs to access, share, and integrate resources (Beirão et al. 2017) . In this regard, OHCs can facilitate resource exchange among stakeholder. For instance, members of the diabetes communities shared their up-to-date information and experience about using wearable devices (e.g., Continues Glucose Monitors (CGM), Dexcom and sport watches) for self-monitoring their health condition and reduce the burden of living with diabetes and improve quality of life. The Experience of commonality in OHCs provides opportunities for members to feel that they are not alone. Hence, the experience of commonality is associated with positive mental health, improving emotional wellbeing Members of the diabetes communities perceived these online platforms as great places to tackle the feeling of loneliness and isolation. Especially in the current situation of the global outbreak of COVID-19, these online communities are ideal places to tackle psychological distress and depression. At this particular point in time, diabetic patients need to strengthen their sense of community by connecting and supporting each other in the OHCs. Because of the nature of OHCs, Aghdam & Watson 2020, Wellington Towards Empowering Diabetic Patients which provides access to information and coordinated social interactions, the members of these communities benefit an alternative solution and needs such as improving their wellbeing (Zhao et al. 2015) . Emotional support directly impacts on the ability to self-manage diabetes and equally selfmanagement of diabetes influences emotional wellbeing (Schiøtz et al. 2012) . Sharing the same situation and stories with other members is another aspect of emotional support. Sharing the same stories creates a shared sense of meaning and community for users. In the Reddit diabetes communities, a large number of users encourage peers in their self-management of diabetes. Patients also reported that sharing monitoring data such as blood glucose and weight makes them feel empowered and motivated. Members of these communities' support each other in coping with social and emotional barriers, staying motivated to reach their goals, and encourage better self-care habits without fear of judgement or stigma. Improving the emotional wellbeing of diabetes leads to better self-care, overcoming psychological barriers, and ultimately, a better quality of life. OHCs are ideal places for brainstorming solutions by members. We identified brainstorming of potential solutions to address daily challenges as another co-creation behaviour occurred in diabetes online communities. Virtual brainstorming is one of the most significant benefits of OHCs for diabetic patients. It provides an opportunity for community members to contribute new ideas to address diabetic daily challenges such as carrying medical equipment, diabetic's workplace problems, injection, and sleep problems. This was identified in many threads posted by the members of the communities. Hence, OHCs are ideal places to brainstorm potential solutions to address these issues. As it can be viewed in Table 1 , Reddit patient suggests a solution to another patient, who is struggling with carrying diabetes bag in public and private business areas. These types of solutions are another example of value co-creation behaviour within diabetes online communities. Participating of community members in brainstorming activities, make them feel that their contributions are valuable and their ideas will help peers to tackle some daily challenges. Because of the high number of demands for DGEP, patients need to be in a waiting list before joining the program. While they are in a waiting list, they can communicate with discharged patients and use their experience. The resource exchange help patients reduce their stress and better prepare for the program. During the program patients, share their experiences and health-related stories with peers, encouraging each other to reach their health-related goals. During this phase, OHC can play an important role as an online interactive platform to facilitate patient-to-patient and patient-to-HCP interaction. After discharge from the program, patients still need to stick to their plans and selfmanage their diabetes. OHCs provide opportunities for them to keep connected to the program, interact with HCPs and share their experience of the program with patients, who are in the "prior-tojoining" phase. Figure 1 , demonstrates the proposed framework for diabetes online communities. Aghdam & Watson 2020, Wellington Towards Empowering Diabetic Patients In terms of the validity and utility of the proposed framework, we conducted expert interviews. A qualitative assessment of the framework flexibility was carried out through interviews with healthcare professionals and the diabetes program coordinator at the QUT clinic. Two health experts, who are directly involved and organised the DGEP, and have more than ten years of experience in the healthcare domain initially evaluated the framework and provided their feedback and suggestions. OHCs are proper educational platforms that lead to better health outcomes and members can learn more from others on how to better manage their health conditions (Chen et al. 2019 ). Information that shared by patients in OHCs benefits other patients by learning from peers, improving their self-management of disease, and ultimately, improving their health (Yan and Tan 2014) . The proposed framework focused on patients as active agents in the process of online value co-creation. Patients are pivotal stakeholders in our framework that can co-create value by resource exchange and social support. In our framework, diabetic patients participate in different forms of value co-creation through informational, social, and emotional support. OHCs empower patients to actively engage in co-creation activities 24/7 especially in times of fear, isolation, and uncertainty. This research study has been conducted during the global pandemic of the COVID-19. During this pandemic and isolation time, patients increasingly participate in diabetes online communities to gain and offer emotional support. These easy-access and 24/7 online platforms help patients to tackle psychological issues such as depression, anxiety, and loneliness because diabetic patients have a twofold greater risk of depression (Schram et al. 2009 ). Shared stories and experiences in OHCs make patients feel that they are not alone, strengthening their sense of community by connecting and supporting each other. Digital health platforms such as diabetes online communities have the potential to increase easy access to diabetes self-management interventions and techniques in the lower cost (Rosal et al. 2014) . Furthermore, participating in diabetes group-based education program provides opportunities for patients to meet and discuss with other members of the communities, obtaining social and emotional support (Steinsbekk et al. 2012) . In doing so, in recent years, the Queensland University of Technology (QUT) offer a partnership program to patients who are newly diagnosed or living with the condition long term. This program aims to provide a quality lifestyle intervention and empowering Type-2 diabetic patients to better manage their symptoms. As type-2 diabetes is a self-managed disease, one of the main aims of the program is to keep patients connected to the program after discharge. We Australasian Conference on Information Systems Aghdam & Watson 2020, Wellington Towards Empowering Diabetic Patients adopted Customer-Dominant logic (CDL) as a way to explore overlaps between our findings and the DGEP. CDL is focused on activities and experiences of the customer at three different stages: preservice, service, and post-service (Heinonen and Strandvik 2015) . It is used as a way to extend the customers' perceptions of the offering and to extend market interactions (Heinonen and Strandvik 2015) . Following CDL, we divided the diabetic patient journey into three phases including; (1) prior to joining the program, (2) during the program, and (3) after discharge from the program. In each phase, we identified value co-creation behaviours such as; resource sharing, story and advice sharing, and social and emotional support. Theoretically, we extended the target body of the knowledge in the healthcare service delivery through enhancing the empowerment theory in which, patients are the central facet and healthcare professionals and healthcare organisations are facilitators of the value cocreation process (Funnell and Anderson 2004) . Research studies have overlooked the nuances relationship between empowerment theory, value co-creation, and the role of OHCs as facilitators for this process. This study provides an opportunity for leveraging peer-to-peer support within digital health platforms such as OHCs to empower patients in their self-management of diabetes. Practically, our findings further provide recommendations to the healthcare industry on how to effectively contribute to the online intervention by shifting from traditional dyadic interaction between healthcare professionals and the patient to online co-creation among all stakeholders. We believe that healthcare providers can potentially use our theoretical and empirical findings to extend the value of the face-toface diabetes group-based education programs by keep patients connected to the program 24/7 regardless of their geographical distance with lower cost. Our study is not without limitations, yet these limitations provide interesting avenues for future research. Our data were gathered from Reddit diabetes online communities. We selected three popular diabetes communities on the Reddit to analyse the contents and interactions among members. We might overlook some small communities related to type-2 diabetes. Furthermore, we only used Reddit as our data collection source. Future studies can focus on more diabetes online communities, aiming that how can a fully functional assistive artefact be designed for diabetic patients, using the design science research guideline (Miah 2008; Miah et al. 2019) . Although the face-to-face diabetes education program held in Queensland, Australia, it can be generalised to any other organisational or country context (For example, in decision support implementation (Ali, Miah and Khan, 2018) ensuring empowering end users). Our future study will extend the current framework by conducting interviews with the members of the communities to identifying their current level of engagement with OHC, identify benefits and challenges of using these platforms, and investigate their online value co-creation behaviour. Therefore, there are some areas required for further research. Another future avenue is to investigate the perspective in which healthcare organisations indirectly participate in online value cocreation. Experimental design studies of OHCs to explore the behavioural and psychological aspects of social support could also be useful. In this research study, we sought to extend the current understanding of the potential of diabetes online communities in empowering self-management for diabetic patients. As such, the main aim of this study was to investigate the potential practices of online diabetes communities to empower selfmanagement of diabetic patients in their health journey. Findings show that patients in diabetes online communities share information, experiences, stories, and potential solutions. They actively participate in online activities regarding offering and receiving support from peers. The vast majority of the shared contents on diabetes online communities include lifestyle-related advice such as diet, exercise and using wearable technologies to better monitor and care of diabetes. Members of diabetes online communities contend that these online forums are ideal platforms to obtain social and emotional support from peers. Our findings, which investigated the connection between Diabetes online communities' practices and outcomes and the real-world DGEP case can further assist healthcare organisations to effectively contribute to the online intervention and extend their communication channel from a traditional power balance between HCO and patients to interactive platform that enables all stakeholders to actively engage in value co-creation activities. As discussed, type-2 diabetes is a chronic disease that needs ongoing self-care and self-manage. OHCs provide opportunities for them to encourage each other in regards to sticking to their self-monitoring and selfmanagement. This is especially true when they discharge from the DGEP and have no access to faceto-face interactions. 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A Systematic Review with Meta-Analysis Diabetes Management through Remote Patient Monitoring: The Importance of Patient Activation and Engagement with the Technology An Evaluation of a Self-Management Program for Patients with Long-Term Conditions Improving Chronic Illness Care: Translating Evidence into Action Analyzing and Predicting User Participations in Online Health Communities: A Social Support Perspective Feeling Blue? Go Online: An Empirical Study of Social Support among Patients Patient Value Co-Creation in Online Health Communities: Social Identity Effects on Customer Knowledge Contributions and Membership Continuance Intentions in Online Health Communities Empowerment Theory This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 New Zealand, which permits non-commercial use, distribution, and reproduction in any medium 


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   key: cord-254494-wbfgrez1 authors: Shi, Chunhong; Zhu, Haili; Liu, Jun; Zhou, Jian; Tang, Weihong title: Barriers to Self-Management of Type 2 Diabetes During COVID-19 Medical Isolation: A Qualitative Study date: 2020-10-14 journal: Diabetes Metab Syndr Obes DOI: 10.2147/dmso.s268481 sha: doc_id: 254494 cord_uid: wbfgrez1 PURPOSE: Diabetes self-management behaviors are necessary to obtain optimum glycemic control, reduce the risk of complications, and improve health outcomes. The COVID-19 pandemic imposes an additional struggle for self-management by diabetes patients. Although previous studies have reported socio-demographic, behavioral, psychological, and cultural barriers to diabetes self-management, little is known about perceived barriers to diabetes self-management among patients during isolation following their recovery from COVID-19. The purpose of this study was to explore perceived barriers among type 2 diabetes patients during isolation following their recovery from COVID-19. PATIENTS AND METHODS: A qualitative, exploratory, and descriptive research design was utilized. Semi-structured telephonic interviews were conducted with 12 patients with diabetes who had been discharged from one COVID-19 designated hospital and underwent isolation in the designated facilities in Wuhan City, Hubei Province, China. Data were analyzed using Colaizzi’s seven steps. RESULTS: Barriers to diabetes self-management identified by patients with diabetes during isolation were categorized into five major themes: inadequate knowledge and behavioral beliefs, shortage of resources, suffering from health problems, negative emotions, and lack of support. CONCLUSION: Perceived barriers to diabetes self-management described by diabetes patients indicated a lack of environmental resources and support strategies to meet their needs. Efforts to remove barriers are important in assisting patients with diabetes to improve their quality of life and health outcomes. Coronavirus disease 2019 (COVID- 19) , which was declared a Public Health Emergency of International Concern by the World Health Organization (WHO) on 30 January 2020, has posed a severe threat to global public health. 1,2 Diabetes mellitus (DM) is a common chronic disease in China with a prevalence of 10.4%. 3 Although people of all ages are generally susceptible to COVID-19, patients with diabetes are at higher risk for COVID-19 due to the multiple concomitant chronic diseases and immunosuppression. 4, 5 According to the currently published literature, the prevalence of DM among COVID-19 patients and critically ill COVID-19 patients were 7.4-20.0% [6] [7] [8] [9] and 17%, 10 respectively. The Chinese Center for Disease Control and Prevention (China CDC) has stipulated that COVID-19 patients discharged from hospitals are subject to a 14-day period of isolation and medical observation. 11 As of midnight on August 19, 2020 , the total number of confirmed COVID-19 cases had reached 84,895 in China. 12 These facts indicated that a large number of COVID-19 patients with diabetes underwent isolation after being discharged from hospitals. Patients with diabetes recovering from COVID-19, who experienced the chronic hyperglycemic state and persistent inflammatory states, are at higher risk of COVID-19 reinfection and the occurrence and progression of DM complications. 13 There is a compelling need for this vulnerable population to reduce this risk through good blood sugar control during their isolation. However, ideal blood sugar levels cannot be maintained solely by anti-diabetic medications; 14 good self-management behaviors play a crucial role in DM treatment-especially for those with type 2 diabetes mellitus (T2DM). 15 Self-management refers to long-term, and effective decisions and behaviors, to maintain patients' well-being, which involves medical, behavioral, and emotional management. 16 Positive and effective self-management not only alleviates the progression of DM on physiological indicators but also improves the patients' quality of life. 17 Scholars from Stanford University pioneered the application of the concept and methods of self-management in a community-based diabetes self-management program. 18 These early studies have opened new channels for the prevention, control, and treatment of DM and substantially improved the quality of life of patients with diabetes. 19 Promoting effective diabetes self-management has long been a challenging issue for the health systems, healthcare providers, community workers, and patients with diabetes. 20 Although the data regarding diabetes management for T2DM patients recovering from COVID-19 during isolation remain scarce, notably, previous studies have reported that among Chinese T2DM patients, only 22.76%-40.09% have achieved optimal glycemic control (hemoglobin A1c level<7.0%, 53 mmol/mol) 21-23 and 9.20%-16.43% have manifested good self-management behaviors. 21, 24 This raises the issue of how to identify factors that hinder diabetes selfmanagement and to address these potential barriers. Studies in developed countries such as the United States, Canada, the United Kingdom, and Singapore have found that common barriers to self-management include poor communication between patients and healthcare providers, limited accessibility to healthcare facilities, lack of family support, inadequate disease knowledge and limited disease treatment methods, lack of motivation for change, physical and cognitive disorders, limited access to diabetes education, and financial barriers. [25] [26] [27] [28] [29] [30] [31] [32] Evidently, factors that hinder diabetes self-management are complex and multifaceted. However, the barriers to diabetes self-management for patients with diabetes recovering from COVID-19 during their isolation are not precisely known. To date, a considerable amount of literature on glycemic treatment and control in COVID-19 patients with preexisting DM has been published. 33, 34 Most studies, however, focused on hospital and physician practice, while few studies investigated or mentioned self-management among patients with diabetes during their isolation following recovery from COVID-19. A qualitative study is an ideal design for an in-depth understanding of the feelings and experiences of patients with diabetes. Such studies are of great significance to elucidate the perceived barriers to diabetes self-management among isolated patients. This study addressed a gap in this field by interviewing patients with diabetes subjected to medical isolation after recovering from COVID-19 to gain a deeper understanding of the barriers to diabetes self-management, and provide new perspectives and approaches for the design of interventions and formulation of policies. This study adopted a descriptive qualitative methodology to collect data through telephonic interviews, which provided a rich and thick description of the participants' perceptions of barriers to diabetes self-management. A phenomenological approach was used to achieve an indepth understanding of the factors hindering diabetes selfmanagement from the patient's perspective. 35 Participants were recruited through purposive sampling based on the following inclusion criteria: (1) T2DM patients with a disease duration of greater than 1 year, (2) COVID-19 patients with diabetes after being discharged from the hospital, (3) had stayed at designated isolation sites for at least 7 days, (4) spoke and understood Chinese (Mandarin), and (5) agreed to participate in the study. Patients with type 1 DM or younger than 18 years old were excluded. The primary researchers of this study, who were nurses at a designated COVID-19 hospital in Wuhan City, Hubei Province, China, contacted patients who met the inclusion criteria through the contact information listed on their medical records. The sample size was determined by data saturation-when no new information was obtained during the last two interviews. 36 Variations in age, education level, and duration of diabetes were considered to ensure diversity in the perception of barriers to self-management. We followed the consolidated criteria for reporting qualitative research to report the findings of this study. 37 Semi-structured, in-depth telephonic interviews were conducted from February 20 to March 4, 2020, at a convenient time after dinner (approximately 19:00-20:00 Beijing Time) in a quiet and comfortable environment. Before each telephonic interview, the primary researchers explained the objectives and methods of the study to the participants, promised to perform confidentiality measures, and obtained verbal informed consent from all participants. All interviews were recorded using a cellphone and a recording pen (Newsmy V29, 16 GB internal memory) with the consent of the participants. An interview guide (Table 1 ) was used to conduct the interviews, which consisted of a series of open-ended questions regarding the various aspects of self-management. The interview guide was tested using pre-interviews with two patients of diabetes not included in the actual study, which resulted in corrections of the language and content. During the formal interviews, the interviewees were encouraged to express their thoughts and perceptions thoroughly and probing questions, such as, "Can you please elaborate on this?" were included to increase the depth of the discussion. The nonverbal information (eg, tone of voice, pause) and the important statements stressed by the patients were documented during the interview. Each interview lasted between 15 and 30 minutes. Each audio recording was transcribed by a co-author within 24 hours of the interview and reviewed by another author who interviewed the patients to ensure accuracy of the transcript. The interviews, raw transcripts, and data analysis were conducted in Mandarin Chinese. Data analysis was conducted by two co-authors using Colaizzi's seven-step method 38 to extract themes and sub-themes. The detailed steps were as follows: (1) reading and re-reading raw data transcribed from the audio recordings; (2) marking and extracting significant statements pertaining to the investigated phenomena; (3) coding recurrent important viewpoints; (4) summarizing all coded viewpoints; (5) elaborating and articulating the meanings of the viewpoints; (6) integrating, categorizing, and refining similar viewpoints into themes; and (7) returning the formulated themes to the interviewees for validation. All authors agreed with the data analysis results. To ensure the rigor of the study, the four criteria of dependability, credibility, transferability, and confirmability were In this study, 12 participants were interviewed. Table 2 shows the demographic information of the participants. Barriers to diabetes self-management were categorized into five themes: inadequate knowledge and behavioral beliefs, shortage of resources, suffering from health problems, negative emotions, and lack of support, as indicated in Table 3 . Respondents in the study were found to have poor knowledge, inadequate self-care behavior and low-level beliefs regarding diabetes self-management. The theme "inadequate knowledge and behavioral beliefs" emerged from all discussions that contained three sub-themes, namely, limited diabetes knowledge, confusion about taking medications, and low adherence to self-monitoring of blood glucose. Most participants (n=11) alluded to the fact that inadequate diabetes knowledge challenged their management of blood glucose. They often asked for help from those around them (eg, daughter or father). They had limited knowledge regarding diet management and physical exercise. Some of them even believed that refraining from sweets and carbohydrate-rich foods or insisting on physical exercise alone could achieve good glycemic control. One female patient stated, "My knowledge regarding diabetes has been gained from my daughter, who is a nurse. She told me which foods I can or cannot eat." (P6) Another male participant stated, "My dad also has diabetes. He controls this disease through exercise and obtains good outcomes, so I control my blood glucose by exercising." (P2) A similar view was expressed by another patient, "I know a little about diabetes. I pay little attention to it in daily life and just engage in exercise to control my glucose." (P9) All participants voiced their concerns about medication treatment. More than half of the patients were unfamiliar with the use of hypoglycemic agents. They were confused about taking medications, with most uncertainty involving the names, usage and side effects of the medications, which prevented participants from effectively managing their disease. A female patient expressed unfamiliarity with the usage of hypoglycemic agents: I am worried whether I take too much acarbose. I take two tablets with each meal, and I do not know if it is too much . . . The doctor told me to alternate between metformin and acarbose, which made me confused. (P7) A male patient stated, The hypoglycemic medicines prescribed by the doctor when I was discharged from hospital were different from what I used at home; maybe the effects are the same. I do not know whether these medicines are better or worse than the previous ones, I cannot judge them. (P4) Low Adherence to Self-Monitoring of Blood Glucose Among all patients, only one brought test strips and needles to the isolation site. They paid little attention to blood Most of the isolation facilities were converted from hotels or high school premises at short notice in response to the demand during the COVID-19 pandemic period. The shortage of resources at these facilities was another issue discussed by all patients. This theme consisted of four subthemes: limited space for exercise, unavailability of blood glucose monitoring, absence of a diabetic diet, and undersupply of hypoglycemic medications. At the isolation sites, the participants were largely confined to their rooms because of social distancing policies. All participants described that they exercised daily but could only do so in their rooms or corridors. As a male patient's transcripts showed, Regular blood glucose monitoring is essential for glycemic control in diabetes. Among all interviewees, only one had performed daily blood glucose monitoring; the remaining participants mentioned that they had not monitored their blood glucose at the isolation sites due to the unavailability of blood glucose monitoring. An elderly female patient stated, All participants were concerned with diet, which is a crucial tool for managing T2DM. 40, 41 In particular, 5 participants clearly expressed that the diet provided at the isolation sites was unsuitable for patients with diabetes. As stated by Participant 12, "Many food items at the isolation site contain sugar . . . I have no choice but to avoid food items with sugar . . . There is no diabetic diet." (P12) Another female patient further added, Approximately half of the participants faced issues regarding the shortage of hypoglycemic medications, or medication changes, due to the non-supply of medications at the isolation sites. One participant mentioned, Another female patient stated, "The medicines prescribed by the hospital are not enough, I don't know if they can last till the end of the isolation period" (P8). The participants described that they experienced hyperglycemia, physical discomfort, and insomnia during the mandatory isolation after contracting COVID-19, which discouraged them from self-managing the diabetes and reduced their motivation to self-manage their diabetes. Suffering from health problems is an important obstacle to adherence to self-management behavior. Two thirds of the participants stated that their blood glucose levels increased and became difficult to control after contracting COVID-19. The unsteady blood glucose made them feel frustrated and impeded their self-efficacy in their journey of diabetes management. As described by one participant, The elevation of blood glucose after contracting COVID-19 was also mentioned by another female patient. "After getting COVID-19 . . . My blood glucose was above 20 [mmol/L]. It has never been so high over the last 20-odd years." She continued, "Blood glucose is difficult to control; I can hardly manage it well." (P12) Of note was that half of interviewees still experienced physical discomfort after COVID-19 treatment and hospital discharge such as tiredness, shortness of breath, aches and pains, or a headache. These physical symptoms prompted them to focus on COVID-19 recovery and treatment while ignoring the self-care of diabetes. Another patient also experienced physical discomfort. Nearly half of the participants experienced insomnia at the isolation facilities as they were unaccustomed to their isolation environments, subjected to activity constraints, and engaged in fewer social activities. Insomnia led to their fatigue, poor concentration, and tension during the day and disrupted their diabetes management routine. The following examples demonstrated this experience. High contagious infectivity, potential fatality of COVID-19, loneliness in the isolated room, and difficulties in maintaining blood glucose levels elicited negative emotions in the participants. Three quarters of patients with diabetes expressed unpleasant or unhappy emotions toward COVID-19 and the isolation environment. Such emotions can cloud their judgments and reduce rationality in decision-making on self-management behaviors. Negative emotions as a barrier to self-management, emerging from the transcripts, included three sub-themes: stigma, dissatisfaction, and anxiety. Participants may have perceived stigma for suffering from COVID-19. They feared discrimination from others and avoided full disclosure about their disease to both peers and healthcare workers, thereby influencing the way they view the disease and approach their self-management. A female patient expressed, The isolated patients faced various inconveniences at the isolation sites. Some of them complained about the lack of supplies (especially medications) and expressed dissatisfaction with the living conditions and diets provided at the sites. Dissatisfaction affected their activation of diabetes self-care and discouraged their behaviors toward diabetes self-management. One participant complained, "The isolation site offers nothing just serves for isolation . . . There's no fruit, no medicine . . . There are too many difficulties for us to manage diabetes." (P8) A male participant expressed his dissatisfaction toward the isolation site, This place isn't as good as the hospital, the room is really tiny . . . the (medical) service here (isolation site) isn't so professional compared with the hospital . . . I just try to control my blood sugar by eating less food. (P9) Patients with diabetes often felt stressed and worried about the medication, diabetes supplies, and blood sugar levels. A third of the patients expressed that they were somewhat worried or anxious. This emotional distress often brings about negative consequences for diabetes and further affects their self-management behaviors indirectly. A participant stated, Most patients with diabetes who underwent forced isolation perceived a lack of guidance and support. These patients described their experiences as a struggle to trudge along a difficult path of diabetes self-management, as they were unable to seek help from anyone under the constraints of social isolation. Lack of support as a theme was expressed by most respondents, which had two subthemes: lack of professional guidance, and lack of family support. Most healthcare providers at isolation facilities had been temporarily extracted from various healthcare departments, who might have had little diabetes knowledge and only took responsibility for COVID-19 prevention and education. The participants expressed the view that they felt helpless with regard to managing their diabetes without professional guidance. For instance, a participant stated, "Every morning, [healthcare providers] only ask if we feel comfortable and measure our body temperature . . . blood glucose is not monitored at the isolation site." (P7) Another patient complained that "The doctors here show little concern for us . . . the healthcare providers differ from those at the hospital in terms of professional levels." (P6) The COVID-19 isolation policy prohibits face-to-face visits from family members, which greatly affects the patient's access to family support. In addition, COVID-19 is characterized by familial aggregation, which also reduced the sources and types of family support provided to the participants. As stated by a divorced female participant, During the isolation period, I have made no phone calls to my family and friends . . . my family members are also staying at the isolation sites, so it is too inconvenient . . . Another participant expressed that she could not get actual assistance from her family members as they could only express their concern over the phone, "The concern from my family is of no use . . . sometimes they can't even send things to me because non-staff entering the isolation site is forbidden." (P12) This exploratory and descriptive qualitative study reported the barriers to self-management of T2DM patients who had recovered from COVID-19 during medical isolation. Five major themes were identified: inadequate knowledge and behavioral beliefs, shortage of resources, suffering from health problems, negative emotions, and lack of support. Self-management is essential for prognosis and glycemic control in patients with T2DM. Understanding the barriers to self-management will help patients make changes and better manage their diabetes. Our results showed that limited knowledge regarding DM is a major barrier to diabetes self-management. Participants tended to gain diabetes knowledge from the experiences of people around them. The common assumption was that low educational levels (average below high school) and old age (mean age: 59.75 ±7.93 years) limited their abilities to acquire medical information and seek better healthcare resources. Similarly, studies conducted in Ethiopia 42 and Iraq 43 have indicated that a lack of appropriate information/knowledge hinders self-management among patients with diabetes. A study by Ji et al showed that diabetes knowledge is positively correlated with overall self-management behavior. 23 Specifically, the higher the level of knowledge on diabetes, the better the self-management behavior of patients with diabetes. 44 Additionally, most patients also expressed their confusion about taking medication. Low education and lack of diabetes knowledge might provide a possible explanation for this. Previous studies have indicated that difficulties and frustrations in taking medications prevented diabetes patients from effectively self-managing. 45 In addition, low adherence to self-monitoring of blood glucose posed another barrier to diabetes self-management, which was consistent with the findings of Tewahido et al 42 and Mikhael et al. 43 This is more commonly associated with the patients' economic position, fear of needles, the erroneous belief that blood glucose will remain normal with timely medicating, physical activity, and dietary modifications. A study by Ji et al 21 also demonstrated that blood glucose monitoring was the lowest priority of patients with diabetes when compared to medications, diet, and physical activity. The results of this study emphasized the importance of improving self-management knowledge and behavioral beliefs in patients with diabetes. Efforts directed toward practical and person-centered diabetes selfmanagement education and support programs are necessary to improve patients' knowledge and behavioral beliefs and self-management levels. A shortage of resources was frequently identified as the key factor that inhibited diabetes self-management in this study. Issues such as limited space at the isolation sites, unavailability of blood glucose monitoring resources, absence of a diabetic diet, and undersupply of hypoglycemic medications, were repeatedly mentioned by the participants. For instance, some participants expressed that the standardized diet at the isolation sites led to the inability to perform self-management in accordance with their specified nutrition plans. This finding was consistent with previous findings that residing in a community with limited healthy foods and the absence of safe exercise environments may be an important barrier to diabetes self-care and glycemic control. 46, 47 For all participants in this study, the provision of resources needed for diabetes selfmanagement by the isolation facilities was a significant issue. However, as was widely recognized, the locations used for isolation of COVID-19 patients had a unified layout and lacked the facilities conducive to diabetes selfmanagement. This finding suggests that creating a favorable environment for self-management of chronic diseases at the isolation sites, such as the provision of a diabetic diet and blood glucose monitoring as part of a daily health management program, is extremely important for the improvement of the quality of life and health of patients. Suffering caused by the disease was a great barrier that emerged from the transcripts. This is consistent with the findings of Hu et al, 45 in which patients' physical suffering kept them from properly managing their disease. Moreover, the results of the present study provided additional evidence that COVID-19 may result in elevated blood glucose levels, which was congruent with the findings reported by Ilias et al 48 and Brufsky. 49 Persistently high blood glucose may cause frustration in patients, thereby affecting their passion towards self-management. Five participants in this study stated that they suffered from severe insomnia. In keeping with our findings, Xue et al 50 also reported significant sleep problems (eg, difficulty falling asleep, early awakenings) in the forced isolation population. In addition, poor sleep quality has been found to be significantly associated with decreased adherence to dietary, lower self-care adherence, and poorer diabetes control. 51 Given disease related suffering, it is imperative for healthcare and COVID-19 isolation organizations to develop and implement strategies to deliver continuous care for discharged COVID-19 patients, especially those with diabetes. Negative emotions were discussed as a psychological barrier to self-management. Half of the participants felt stigmatized, which was mainly manifested as societal rejection; one-third complained about poor service at the isolation sites, and one-third expressed anxiety. Although the public health response to COVID-19 has been essential in preventing and containing the epidemic, it may also have aggravated the stigmatization of patients. 52, 53 Forced isolation and the associated measures have disrupted the social lives of patients with diabetes, resulting in them feeling fearful and trapped. Armitage et al 54 reported that social isolation exposes older adults to greater risks of negative emotions such as depression and anxiety. An online study conducted in Italy reported that longer isolation times, combined with smaller physical spaces, led to a deterioration in mental health. 55 Moreover, psychological distress affected the medication adherence and self-management of patients with diabetes. 31 Kato et al 56 found that the nonadherence behaviors of patients with diabetes may be a response to the internalization of stigma. Self-stigma is a negative independent factor that affects the self-care behavior of patients with T2DM. 57 Our results confirmed these findings and suggested that greater emphasis should be placed on the mental health of this vulnerable population, and healthcare and COVID-19 isolation organizations should adopt multifaceted strategies to eliminate potential drivers of negative emotions in isolated patients. This study revealed that the lack of professional guidance from healthcare providers (eg, self-care measures, maintenance of target blood glucose, monitoring of complications) is a common barrier to diabetes selfmanagement. Healthcare providers play a unique role in delivering person-centered diabetes self-management education, supporting interventions, and assisting patients to undertake protective self-care behaviors. 58 Other qualitative studies have reported similar findings whereby patients with limited resources were particularly challenged when seeking medical services or obtaining care and support. 59, 60 Apart from the scarcity of guidance from healthcare providers, the participants also identified the lack of family support as another barrier to diabetes selfmanagement. During the isolation period, it is difficult for diabetes patients to obtain knowledge, care, and material support from their family members, although this support was essential for promoting lifestyle changes and improving self-management behavior in patients with diabetes. 23 Such a result matches the findings of previous studies, which considered family members, friends, and peers of patients with diabetes as primary promoters of selfmanagement. 30, 59, 61 Similarly, quantitative studies have also indicated that a higher level of social support is associated with better adherence to recommended selfmanagement behaviors. [62] [63] [64] In conclusion, there was insufficient support to encourage diabetic selfmanagement of the isolated patients. Such problems may be resolved by establishing electronic blood glucose records and a remote consultation system to provide practicable diabetes self-management education and support, and by enhancing telephonic and internet-based family support. This study had several limitations. First, we obtained data from a small geographical area (Wuhan City) and a small, convenient sample (12 patients with diabetes), which might limit the generalizability of the findings. Second, our analysis was based on interview data. Therefore, it was impossible to explore the differences between the demographic characteristics (such as gender and education level) of the barriers to diabetes selfmanagement. Third, this study explored barriers to diabetes self-management from the patients' perspectives, without considering the experience of healthcare providers and family members. Fourth, qualitative studies have inherent limitations, such as the tendency for subjectivity during data analysis. Future research should collect data from larger samples or adopt a multicenter approach to obtain a broader view of barriers to diabetes self-management. Our findings provide insight into barriers to diabetes selfmanagement among T2DM patients during isolation following recovery from COVID-19. We found that inadequate knowledge and behavioral beliefs, shortage of resources, suffering from health problems, negative emotions, and lack of support were barriers to self-management among patients with diabetes. Understanding these barriers is beneficial for the formulation of targeted strategies, such as creating favorable isolation environments, strengthening medical and social support, and implementing patient-centered diabetes care, to promote successful self-management. At present, as many countries around the world are still in the critical period of pandemic prevention and control, greater concern should be paid to patients with diabetes during isolation. In addition, open dialogue among patients, healthcare providers, family members, and policy makers can be established to better support patients' diabetes journey and improve health outcomes. This study was approved by the Ethics Committee of Hunan Academy of Traditional Chinese Medicine Affiliated Hospital (Approval No.202003-09). We explained the objective, process, and methods of the study to the participants and obtained verbal informed consent prior to each telephonic interview. Participants were assigned anonymous identification numbers (P1, P2, etc), and personally identifiable information was deleted from the transcripts to protect patient privacy. The interview data were kept strictly confidential, and all audio recordings and transcripts were stored in a passwordprotected computer. Interviewees were free to withdraw from the study at any time without any reason. 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Furthermore, we wish to express our gratitude to the Hunan Academy of Traditional Chinese Medicine for providing financial and material support. Finally, we thank our advisors Dr. Chunyan Li and Dr. Yinhua Zhang for their contribution of valuable insights in the process of this study. The authors report no conflicts of interest in this work. 


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   key: cord-255687-jud875xc authors: García-Villasante, Eilhart; Baca-Carrasco, Víctor; Gutierrez-Ortiz, Claudia; Pinedo-Torres, Isabel title: Diabetes care during COVID 19: Experience in telemedicine from a developing country date: 2020-08-04 journal: Diabetes Metab Syndr DOI: 10.1016/j.dsx.2020.07.046 sha: doc_id: 255687 cord_uid: jud875xc nan Please cite this article as: García-Villasante E, Baca-Carrasco Ví, Gutierrez-Ortiz C, Pinedo-Torres I, Diabetes care during COVID 19: Experience in telemedicine from a developing country, Diabetes & Metabolic Syndrome: Clinical Research & Reviews (2020), doi: https://doi.org/10.1016/ j.dsx.2020.07.046. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Dear Editor, We have read with interest an article published in this journal (1) . The authors detail with accuracy the main telemedicine problems and most of them are being seen in our country. We work at Endocrinology department in a reference hospital in Perú which is in fifth position of confirmed cases of COVID 19 worldwide (2) . Our main concern is about diabetic patients because they are at major risk to get infected and develop severe forms of disease (3). The use of telemedicine in Peru is incipient. On March 2020, the Peruvian Ministry of Health stablish the official pathway for its implementation. Since then, teleconsultations have been developing slowly and not uniformly in the health centers. According to our national data, almost 60% of the population belongs to the lowest socioeconomic strata (4) and they gain less than 240 dollars per month, so many patients do not have smartphones and, if they do, are lacking technology skills. Therefore, some of them prefer to speak on regular cellphone line or even on landline which make difficult to see patients' expressions and use non-verbal communication. On this last point, gestures are a basic tool to express very useful thoughts for patients with few language skills or fear and insecurity to express their doubts. This aspect of communication can also be ignored in the different platforms used for teleconsultations, so health professionals should be trained in compensatory strategies to overcome the physical distance (5). Also, in the publication is not been considered the importance of the health institution creating systems for the safe delivery of medications avoiding COVID-19 infection. We coordinate with the insurance office and pharmacy department so that a family member can approach to receive the medications. Currently, we have a project in place to decentralize the delivery of medications to primary care centers where viral load by COVID 19 is lower. Pitfalls in telemedicine consultations in the era of covid 19 and how to avoid them Reported Cases and Deaths by Country, Territory, or Conveyance Risk factors for mortality in patients with coronavirus disease 2019 (covid-19) infection: a systematic review and meta-analysis of observational studies. The Aging Male. Available at: Taylor & Francis Online Informe Técnico: Evolución de la Pobreza Monetaria J o u r n a l P r e -p r o o f The authors declare no conflict of interest in this publication. 


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   key: cord-260119-pgu2crhs authors: Golledge, Jonathan; Fernando, Malindu; Lazzarini, Peter; Najafi, Bijan; G. Armstrong, David title: The Potential Role of Sensors, Wearables and Telehealth in the Remote Management of Diabetes-Related Foot Disease date: 2020-08-13 journal: Sensors (Basel) DOI: 10.3390/s20164527 sha: doc_id: 260119 cord_uid: pgu2crhs Diabetes-related foot disease (DFD), which includes foot ulcers, infection and gangrene, is a leading cause of the global disability burden. About half of people who develop DFD experience a recurrence within one year. Long-term medical management to reduce the risk of recurrence is therefore important to reduce the global DFD burden. This review describes research assessing the value of sensors, wearables and telehealth in preventing DFD. Sensors and wearables have been developed to monitor foot temperature, plantar pressures, glucose, blood pressure and lipids. The monitoring of these risk factors along with telehealth consultations has promise as a method for remotely managing people who are at risk of DFD. This approach can potentially avoid or reduce the need for face-to-face consultations. Home foot temperature monitoring, continuous glucose monitoring and telehealth consultations are the approaches for which the most highly developed and user-friendly technology has been developed. A number of clinical studies in people at risk of DFD have demonstrated benefits when using one of these remote monitoring methods. Further development and evidence are needed for some of the other approaches, such as home plantar pressure and footwear adherence monitoring. As yet, no composite remote management program incorporating remote monitoring and the management of all the key risk factors for DFD has been developed and implemented. Further research assessing the feasibility and value of combining these remote monitoring approaches as a holistic way of preventing DFD is needed. Diabetes-related foot disease (DFD), including foot ulcers, infection and gangrene, is one of the 10 leading causes of the global disability burden [1] . About 40% of people who develop DFD Hyperten sion Outpatient blood pressure measuremen t Cuff-less blood pressure monitor [13] Better implementation of anti-hypertensive medications and more frequent monitoring Better informed management of blood pressure and reduced progression of macro and microvascular disease and mortality Abnormal gait Not routinely managed Gait and activity monitor [14] Gait retraining and encouraging remote physical activity Reduce gait abnormalities potentially reducing plantar pressures and ulcer incidence Periphera l artery disease Vascular laboratory assessment using ultrasound or Doppler Foot blood supply sensor [15] Earlier identification of complications and prompt medical management . The diagram outlines the key areas for prevention that can be targeted with sensors, wearables and telemedicine. Table 1 . Examples of sensors and wearables with potential value for preventing DFD. Pre-ulcerative lesions Visits to podiatrist Home foot temperature monitor and mobile phone applications [9, 10] Offloading of "hot spots" following confirmed persistent temperature differences Reduced progression of at-risk sites prone to develop foot ulcers Elevated plantar pressures Offloading footwear Plantar pressure monitor [11] Warning systems to stimulate offloading and better design and modification of footwear Improved offloading with reduced ulcer development Elevated plantar pressures and tissue stress Patient education Footwear adherence monitor [11] Behaviour change support counselling informed by objective data Improved offloading adherence Hyperglycaemia Capillary glucose monitoring Continuous glucose monitor [12] Intensive glycaemic control Better informed management of hyper and hypoglycaemia and reduced progression of macro and microvascular disease Hypertension Outpatient blood pressure measurement Cuff-less blood pressure monitor [13] Better implementation of anti-hypertensive medications and more frequent monitoring Better informed management of blood pressure and reduced progression of macro and microvascular disease and mortality Most foot ulcers develop due to repetitive trauma on the feet of people with a loss of protective sensation, such as those with diabetic peripheral neuropathy (DPN) [2] . Recurrent trauma results in local inflammation, or a "hot spot", which can be detected by an elevated temperature at the affected site [16] . This offers a means to identify people who are likely to develop foot ulcers for immediate foot care, such as the removal of calluses and modifications of footwear, to achieve better offloading to reduce this repetitive trauma and in turn the hot spot [2] . Most previous studies have used infra-red thermometers to measure foot temperature at multiple sites on both feet and compare identical sites on opposite feet [17] [18] [19] [20] . Prior research suggests that a temperature difference between identical sites on opposite feet of >2.2 • C (equivalent to~4 • F) on two consecutive days can accurately predict ulcer development [21, 22] . It has recently been reported that the difference between the median of temperature at six key locations on one foot (the hallux, first, third and fifth metatarsal heads, the mid-foot and heel) and ambient temperature is also able to predict foot ulcer development with an excellent sensitivity, although with limited specificity [23] . This potentially allows people with a unilateral foot ulcer and those with prior unilateral major amputation to also be monitored for the hot spots that are predictive of impending ulcers. Given its predictive value, regular foot temperature monitoring offers the opportunity to instigate urgent offloading and foot care, such as callus removal, to prevent an impending foot ulcer. Four randomised controlled trials have examined the efficacy of daily home foot temperature monitoring to signal the need for offloading in people at risk of diabetes-related foot ulcers [17] [18] [19] [20] . Three of these trials [17] [18] [19] , which were performed by the same team and included a total of 427 participants, reported a significant and substantial reduction in foot ulcer incidence in those allocated to home foot temperature monitoring. The other trial [20] , performed by a different research group and including only 41 participants, reported no significant effect of home foot temperature monitoring and urgent offloading on foot ulcer incidence [20] . A larger randomised trial involving 304 participants is currently examining the cost-effectiveness and cost-utility of home foot temperature monitoring [9] . Recently, a further clinical trial reported on the efficacy of foot temperature monitoring performed at only monthly intervals at an out-patient clinic, rather than at home [24] . A thermal camera was employed to identify "hot spots" in order to advise on interventions, such as reductions in physical activity and improved offloading of the concerned area [24] . The trial included 110 people with a past history of a diabetes-related foot ulcers and reported no benefit of the intervention in preventing foot ulcers or improving health-related quality of life [24] . It is possible that these contrasting findings relate to the less-frequent monitoring of foot temperature performed, which may have missed an opportunity for the early identification of at-risk patients. These findings suggest the potential benefit of applying modern technology to regularly monitor foot temperature remotely in the participant's home in contrast to less frequent monitoring in outpatient clinics. The International Working Group on the Diabetic Foot (IWGDF) recently gave only a weak recommendation for the use of home foot temperature monitoring based on the moderate quality of evidence [25] . This likely reflects the small size of prior trials, limitations in the design of the previous trials and the practical difficulties of implementing home foot temperature monitoring. The previous trials testing home foot temperature monitoring [17] [18] [19] have excluded people with peripheral artery disease (PAD), which is an established risk factor for foot ulceration, thereby limiting the generalizability [20] [21] [22] . Both PAD and DPN have been reported to influence foot temperature [23] . In a recent thermal imaging study, participants with PAD had a significantly higher foot temperature than those that did not have PAD [26, 27] . In contrast, previous studies have reported a positive correlation between foot temperature and ankle brachial pressure index, implying that people with PAD have a lower foot temperature [28] . This disparity might relate to whether people with severe PAD are studied or not. Furthermore, prior clinical experience and recent reports of infrared thermography show that foot temperature rises immediately following successful revascularization in correlation with the increase in the ankle brachial pressure index [29] . Given the established effect of leg ischemia on foot temperature and the exclusion of participants with this problem from prior trials [17] [18] [19] [20] 24] , the role of home foot temperature monitoring in people with PAD remains unclear. The ongoing trial of home temperature monitoring detailed above only excludes people with critical limb ischemia (defined as a systolic ankle blood pressure <50 mmHg, systolic toe blood pressure <30 mmHg or transcutaneous oxygen pressure <30 mm Hg) and therefore will better clarify the role of home temperature monitoring in people with milder forms of PAD [9] . Accepting the need for additional evidence for home foot temperature monitoring in larger numbers of people at risk of DFD with broader inclusion criteria, there are also some practical challenges to implementing this preventative approach. Previous trials have required participants to separately measure temperature at 12 locations on their feet using an infrared thermometer daily [9, [17] [18] [19] . Importantly, all trials to date have used the same type of hand-held device, which has been found to be a time-consuming method and may not be feasible for the majority of people with diabetes, such as those that have impaired vision, impaired mobility or who have multiple comorbidities which all have impacts on self-care motivation. There is therefore interest in developing sensors to better automate home foot temperature monitoring to make this measurement much more user-friendly. The most advanced, currently described system for the automated measurement of foot temperature is the Podimetrics Mat [23, 30] . This is a wireless mat that is designed to remotely monitor the temperature of the plantar surface of the foot with minimal involvement from the patient [30] . If the mat is stepped on for a period of about 20 s, it automatically takes a thermogram of both feet. The thermogram accurately measures temperature over the range of 15 to 40 • C and transmits the data securely to an approved server managed by the manufacturer. Foot temperature asymmetry is automatically calculated based on the thermogram. In a prior study of 129 participants with a past history of diabetes-related foot ulcers, a temperature difference of 2.2 • C between common sites on both feet correctly predicted 97% of foot ulcers, with an average lead time of 37 days and a false-positive rate of 57% [30] . Increasing the temperature threshold to 3.2 • C decreased sensitivity to 70% but reduced the false-positive rate to 32%, with approximately the same lead time of 35 days. About 86% of the participants used the system at least 3 days a week. However, this device is not commercially available outside of the United States of America and may also be too expensive for individual use. Other options for remotely monitoring foot temperature include a thermal camera incorporated into a mobile phone, insole devices or optical fiber based smart textiles, such as smart socks or insoles [10, 27, [30] [31] [32] . Smart phone infrared thermal imaging cameras have excellent agreement with more established infrared imaging systems and thus appear suitable for use in clinical practice [33] . These devices may need more development to allow patients to use them easily at home, and the cost of such devices may be a potential limitation. Smart socks have been tested in small numbers of people with DPN and been shown to be able to accurately and repeatedly measure temperature at multiple sites on both feet [31, 32] . However, whether it is feasible to use these regularly over a prolonged follow-up process is not currently clear and remains to be investigated. A large randomised trial of 300 participants with severe DPN is currently evaluating the effectiveness of daily home-based foot temperature measurements using an intelligent sensor-equipped insole combined with photo documentation in preventing foot ulcers [10] . Results from this trial will provide larger-scale evidence on the value of this approach. DPN leads to loss of intrinsic foot muscles and changes in foot shape [2] . These changes can promote areas of high pressure within the plantar surface of the feet during standing or walking [2] . A prior meta-analysis suggests that people with DPN and a history of foot ulcers have higher plantar pressures during walking than those with DPN who have not had an ulcer [32] . The IWGDF guideline strongly recommended that people with a history of foot ulcers use footwear designed to reduce their high plantar pressures [25] . Plantar pressures are traditionally measured in clinical practice using highly designed pressure plates or insoles with pressure sensors located within health care or research facilities [34] . Systems such as the Pedar ® (Novel, Munich, Germany) and F-Scan™ (Tekscan Inc, Boston, MA, USA) are now available that can reproducibly measure plantar pressures within footwear [35] . These systems have been used to confirm that therapeutic footwear is effective at reducing plantar pressures [35] . They are also being extended to measure plantar pressures and other tissue stress on the plantar surface of the feet during everyday activity [36] . Patient access to such systems is limited, however, as they are only available in a small number of research or clinical settings, require specific protocols for obtaining data and are not available for home monitoring [37] . These systems differ in relation to the types of sensors used to measure plantar pressure; for example, some have large capacitive sensors and others have smaller resistive sensors or piezoelectric sensors which are more temperature-sensitive. Therefore, the user should be familiar with the advantages and disadvantages of each system, as this determines the application and the quality of data obtained [36, 38, 39] . Smart insoles, such as the SurroSense Rx system (Orpyx Medical Technologies, Calgary, Alberta), have now been developed that can monitor plantar pressures and provide alerts directly to wearers [40] . This system consists of a pressure-sensing insole that contains eight pressure sensors: three positioned under the metatarsal heads, two under the lateral plantar surface, one under the heel, one under the hallux and one under the lessor toes. The wearer receives an alert when sustained pressure is detected (pressure exceeding 35-50 mmHg and lasting over a 15-min period) and a pressure map of each foot showing the area where pressure is sustained [40] . The alert thresholds are based on the integration of pressure data over time. The correct therapeutic response to the alert is the offloading of the area with sustained pressure within 20 min of detection. In a study of 17 people with a past history of foot ulcers, those receiving a great number of alerts (at least one alert every two hours) wore their offloading for longer and had better adherence in responding to alerts [40] . Most participants felt that the insoles were useful and achieved good performance [40] . In a recent clinical trial [41] , 58 patients with DPN and a recent history of a plantar foot ulcers were studied. They were randomly assigned to either an intervention group that received audio-visual alerts via a smartwatch linked to the SurroSense Rx insole system and offloading instructions when aberrant pressures were detected or a control group that did not receive any alerts. This trial reported a 71% reduction in ulcer incidence in the intervention compared with the control group (incidence rate ratio 0.29, 95% CI, 0.09-0.93; p = 0.037) [41] . However, this trial had a small sample size and a large dropout of 35% during the wearing-in period of the insole system and a further 50% dropout in the intervention group during follow-up [42] . In addition, the pressure feedback system used recorded pressure at a low sample frequency and failed to measure peak pressures. Importantly, 89% of alerts were received during static weight bearing positions and only 11% during walking in the study [42] . Therefore, the usability and ease of implementing this type of device remains to be demonstrated in well-powered clinical trials. Further evidence is needed for the widespread adoption of home plantar pressure monitoring. Therapeutic footwear specifically designed to the shape of the patients' feet and targeted to reduce >25% of peak plantar pressures is an established part of the management of people with DPN [25] . Such footwear is strongly recommended by the IWGDF guideline [25] . However, prior randomised trials of offloading insoles or footwear have shown inconsistent results, with only four of the eight trials reporting a reduction in the incidence of foot ulcers [43] [44] [45] [46] [47] [48] [49] [50] . A likely contributor to the inconsistent results of these trials is the variation in adherence to offloading. In one of the trials, for example, it was reported that custom-made offloading footwear did not significantly reduce foot ulcer incidence [49] ; however, among the 71 participants that adhered to their custom-made offloading footwear for 80% of the time they were weight bearing, there was a significant reduction in the incidence of foot ulcers of 50% compared to the control group [49] . This emphasizes the importance of adherence to wearing offloading footwear in order for it to be effective. In order to facilitate footwear use, accurate and objective data on adherence are needed. Temperature sensors (thermistors) placed inside therapeutic footwear have been used to monitor offloading use [49] . Combining such sensors along with activity monitors allows footwear adherence as a proportion of daily weight-bearing activity to be estimated [49] . A previous study showed that a temperature threshold of 25 • C to indicate that footwear was worn had a sensitivity of 95%, a specificity of 99%, a negative predictive value of 99% and a positive predictive value of 99% in determining footwear use [51] . Past research also demonstrates that these temperature sensors are a valid method of estimating footwear adherence compared to adherence measured using a time-lapse camera [52] . It is anticipated that small sensors will soon become available that can accurately monitor an individual's footwear use and activity and provide "live" data seamlessly to remotely located health practitioners [53] . This objective footwear adherence data may be used to inform remotely delivered motivational interviewing aimed at increasing the frequency of offloading [54] . Further developments are needed before this approach can be implemented in a remote management program. It should be noted that there is a paucity of commercially available sensors for monitoring adherence easily and accurately, and most of the aforementioned sensors have only been used in a research context [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] . The optimal control of glucose, blood pressure and lipids is frequently not well implemented among people that develop DFD [56] . People with DFD have an increased risk of all-cause mortality (relative risk (RR) 1.89, 95% confidence intervals (CI) 1.60, 2.23) and fatal myocardial infarction (RR 2.22, 95% CI 1.09, 4.53) compared to people with diabetes without DFD [57] . In people with a history of diabetes-related foot ulcers, the risk of cardiovascular mortality is about 50% over 10 years and the annual mortality rate is estimated to be about 6% [58] . This emphasizes the importance of optimizing medical management in this population. Glycaemic control is important for preventing both macro and microvascular complications, and a meta-analysis of past randomised trials suggests that intensive glycaemic control prevents amputations [59] . In clinical practice, diabetes management is usually informed by self-monitoring of blood glucose [60] . Wearable or implantable sensors are now available for the continuous monitoring of glucose [60] ; these use enzymatic technology to monitor interstitial fluid rather than blood glucose [61] . These sensors can measure glucose up to every 5 min non-invasively for a period of about one week, after which most devices need to be replaced [56] . Such sensors have been incorporated into closed loop systems which provide automated insulin delivery to people with type 1 diabetes with improvements in glycaemic control [62] . Recent meta-analyses of randomised trials comparing self-monitoring and the continuous automated monitoring of glucose in people with type 2 diabetes suggest that continuous monitoring facilitates better glycaemic control [61, [63] [64] [65] . The use of such devices is now recommended by the North American guidelines for some patients, such as those with poor glycaemic control (HbA1c ≥ 9%) [66] . A recent trial showed that flash glucose monitoring (measuring interstitial fluid glucose) can be implemented in the primary care environment, although it may not be superior to Sensors 2020, 20, 4527 7 of 15 traditional methods as measured by HbA1c at 12 months [12] . The application of continuous glucose monitoring for people with diabetes who are at a high risk of complications such as DFD may have substantial benefits, but access to this technology is currently limited to selected patients due to the current high expense of such monitoring systems. High blood pressure is another important risk factor for complications in people with DFD. Anti-hypertensive medications, such as angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, have been shown to reduce the incidence of cardiovascular events in people at risk of DFD, such as those with PAD [67] . Control of blood pressure is, however, frequently suboptimal in people at risk of DFD [68] . In a recent study of 2773 people with PAD, about 40% had a systolic blood pressure above the target level of 140 mmHg [68] . Currently, blood pressure is monitored through the assessment of pulsation linked with an inflatable cuff placed around the upper arm. Novel cuff-less wearable devices have now been developed for the estimation of blood pressure and may provide a more practical way of repeatedly monitoring blood pressure and facilitating better management [13, 69] . These devices use varying methods, such as pulse transit time, laser Doppler flowmetry and artery vibration, to calculate blood pressure. Some of these devices are available commercially, such as from TMART Technologies Limited, China and Somnomedics, Germany, and some-but not all-have been shown to accurately measure blood pressure in small numbers of people with comparable results to classical cuff-dependent machines and also intra-arterial assessments [69] [70] [71] . The accuracy and value of these devices in improving the medical management of people at risk of DFD need further evaluation. People at risk of DFD also require lipid control. The intensive lowering of low-density lipoprotein has proven efficacy in reducing major adverse cardiovascular and limb events in people at risk of DFD, such as those with PAD and diabetes [4, 72] . Low-density lipoprotein sensors have also been built, although further development and testing is needed before they will be ready for widespread use [73] . Medication non-adherence is often defined as taking less than 80% of the prescribed treatment [74] . Due to a variety of factors including cost and regimen complexity, adherence to diabetes treatment is often poor and is reported to vary from 23% to 77% across differing populations [75, 76] . In order to achieve optimal control of risk factors, it is important that patients adhere to prescribed medications. Sensors have now been developed that are capable of monitoring medication ingestion; for example, Proteus Discover provides data on medication taking and physical activity to both patients and practitioners [77] . It consists of an ingestible sensor, a wearable sensor patch, a patient mobile app and a provider Web portal. After being swallowed, the ingestible sensor is activated and sends a signal with a specific code that is detected by the patch. When the ingestible sensor pill is taken with medication, it can measure medication ingestion adherence. The patch also can measure activity, heart rate and step count. Data from the patch are transmitted to a mobile device to be viewed by the patient and then to the Cloud and onto a Web portal for a practitioner to view. The mobile device app prompts the patient to take their medication doses as scheduled. A previous study suggested that Proteus Discover can improve control of blood pressure, low-density lipoprotein and HbA1c [77] . Such sensors could have a role in people at risk of DFD, but this needs further testing and consultation with patients and other key stakeholders. There is a lack of head-to-head clinical trials comparing the various types of sensors or monitors available for remote medical management described above; more importantly, the control arms in clinical trials of remote monitoring systems have varied substantially. Therefore, there is an ongoing need to assess the suitability of these sensors for optimizing medical management in people at risk of DFD. People with DPN often have an abnormal gait, which likely contributes to high plantar pressures and the risk of foot ulcers [78] . The assessment of gait is complex, but wearables have now been developed that are capable of monitoring it remotely [79] . Such information can be potentially used for the design of a gait retraining program aimed at reducing plantar pressures and risk of ulceration. Artificial intelligence systems, such as the Gait-Enhancing Mechatronic System (GEMS) (Samsung, Seoul, Korea), have also been developed to improve gait and redistribute foot pressure, although their exact role in health care is not currently clear [80] . Other web-based and remotely delivered methods of physical therapy and rehabilitation may provide further ways to improve gait in people with DPN [81] . A clinical trial is currently in progress to test whether a remotely delivered physical therapy program can improve DPN symptoms and severity as well as gait and function [14] . Artificial intelligence has also been applied to the development of a robotic systems for assessing DPN that are potentially able to screen people for their risk of developing DFD [82] . There is a current Cochrane review that is reviewing the evidence of the accuracy of all potential simple tests for screening DPN to supply more comprehensive evidence [83] . There is also interest in the development of sensors to determine foot perfusion [15] ; the vascular early warning system (VEWS), for example, functions by using infrared optical sensors placed on the toe and dorsum of the foot to measure changes in blood volume within the microvasculature during foot elevation [15] . These sensors have not been tested in well-powered randomissed clinical trials or in comparison to standard care [84] . One challenge with assessing these systems in clinical contexts is that standard care can vary substantially between health services, countries and continents; therefore, the role of such systems in delivering preventative medicine remains unanswered but is an exciting future area of research. It is possible that remotely delivered gait rehabilitation programs may reduce the risk of DFD. For people with DFD, treatment and education typically occur in an outpatient clinic weekly or bi-weekly. Although remote monitoring methods for people with DFD using smartphone applications have been developed, these are still in their infancy and have not been widely tested or implemented [85] [86] [87] . Despite their potential application in remote DFD monitoring, the diagnostic accuracy of mobile phone images is reported to be poor and therefore should not be used as a stand-alone diagnostic instrument for DFD [88] . This is a rapidly evolving area; therefore, novel mobile phone applications and remote monitoring methods may improve over time. Telehealth is an established means of performing medical consultations [89] . The benefit of using telehealth for managing foot ulcers has been demonstrated in several meta-analyses and systematic reviews [90] [91] [92] . Most of the evidence comes from two clinical trials [93,94]: the first trial evaluated the effectiveness of a telehealth intervention made up of 2:1 online:standard outpatient consultations compared to a usual care intervention consisting of three standard outpatient clinic visits on ulcer healing in 374 people [93] . The authors reported no significant difference in ulcer healing or amputation between the two methods but did show an increased risk of mortality in the remote monitoring group (HR = 8.68, 95% CI: 6.9-10.88). This was a surprising finding that was not explained by any of the studied covariates [93] . A more recent cluster randomised controlled non-inferiority trial of 182 adults evaluated telehealth [94] . Weekly telemedicine consultations via an interactive Web-based ulcer record and a mobile phone for communication with the healthcare specialist in addition to outpatient clinic visits every 6 weeks was compared to visiting the outpatient clinic every second week [94] . The trial showed no difference in time to ulcer healing and a superiority in prevention against amputation (mean difference: 8.3%, 95% CI: 16.3%, −0.5%) in the intervention group [94] . An important factor to note in these trials was that the intervention arms all included some face-to-face consultations with a health care professional. Based on anecdotal evidence, at present, there appears to be a range of different approaches to telemedicine that are used globally, ranging from mobile phone-based consultations, hospital-based remote management consultations and the phone-based review of patients. However, how such approaches should be designed in line with face-to face care has not been well defined in the literature. There has been limited study of the value of telehealth consultations in preventing rather than treating DFD. The COVID-19 pandemic has provided a stimulus for studies testing the use of remote monitoring technologies and telehealth consultations in preventing DFD [7, 8] (see Table 2 ). Table 2 . Currently available and required evidence for the remote assessment and prevention of diabetes-related foot disease. Home foot temperature monitor A number of small RCTs show a decreased incidence of foot ulcers in people performing home-based temperature monitoring Lack of a widely tested and user-friendly way of identifying "hot spots" Generalizability from prior smaller studies in select populations [9, 10] Plantar pressure monitor Possible to monitor plantar pressure remotely and use patient alarms to warn patients of impending sites of tissue breakdown as reported in one small RCT Unclear if technology can be further developed to be more user-friendly and whether the findings are applicable and would be effective on a widespread basis [11] Footwear adherence monitor Technology has been developed to accurately measure footwear adherence Need for widespread testing of value of using devices Patients' views on use of adherence monitoring is still unclear [11] Continuous glucose monitor Highly developed area of monitoring and tested in multiple RCTs with proven benefit in improving glycaemic control (HbA1c) Whether this remote monitoring improves outcomes in people at risk of developing DFD remains unclear [12] Cuff-less blood pressure monitor Technology developed to assess this reported to be accurate in a small number of studies Currently unclear whether these devices can be used on a widespread scale [13] Foot blood supply and sensation assessment Technology still in the early developmental stages for monitoring The benefit of these devices in improving clinical outcomes need to be further evaluated in RCTs [15, 82] Legend: PAD = peripheral artery disease, RCT = randomised controlled trial, HbA1c = glycated haemoglobin A1c, DFD = diabetes-related foot disease. Sensors, wearables and telehealth approaches capable of remotely monitoring the key risk factors for DFD have been developed. We believe that the utilization of sensors, wearables and telemedicine approaches outlined in this review-and those currently under development-will offer an innovative means to approach the assessment of risk factors in people with DFD. It remains to be seen what broad impact these can have on the prevention of DFD. The COVID-19 pandemic may provide the stimulus for the innovative and pragmatic large-scale testing of a technological approach to preventing DFD in efforts to keep feet safe, intact and at home. The authors declare no conflict of interest. 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In Handbook of Human Motion Potential Applications of Smart Multifunctional Wearable Materials to Gerontology Smarter Sole Survival: Will Neuropathic Patients at High Risk for Ulceration Use a Smart Insole-Based Foot Protection System? Innovative intelligent insole system reduces diabetic foot ulcer recurrence at plantar sites: A prospective, randomised, proof-of-concept study Preventing foot ulcers in diabetes using plantar pressure feedback Manufactured Shoes in the Prevention of Diabetic Foot Ulcers Effect of Therapeutic Footwear on Foot Reulceration in Patients With Diabetes Shear-Reducing Insoles to Prevent Foot Ulceration in High-Risk Diabetic Patients Custom-Made Orthesis and Shoes in a Structured Follow-Up Program Reduces the Incidence of Neuropathic Ulcers in High-Risk Diabetic Foot Patients A diabetic foot ulcer pilot study: Does silicone gel sheeting reduce the incidence of reulceration? Prevention of Recurrent Foot Ulcers With Plantar Pressure-Based In-Shoe Orthoses: The CareFUL Prevention Multicenter Randomized Controlled Trial Effect of Custom-Made Footwear on Foot Ulcer Recurrence in Diabetes: A multicenter randomized controlled trial Clinical efficacy of therapeutic footwear with a rigid rocker sole in the prevention of recurrence in patients with diabetes mellitus and diabetic polineuropathy: A randomized clinical trial Adherence Over Time: The Course of Adherence to Customized Diabetic Insoles as Objectively Assessed by a Temperature Sensor Validity and feasibility of a temperature sensor for measuring use and non-use of orthopaedic footwear New Monitoring Technology to Objectively Assess Adherence to Prescribed Footwear and Assistive Devices During Ambulatory Activity Adherence to wearing therapeutic shoes among people with diabetes: A systematic review and reflections Leveraging smart technologies to improve the management of diabetic foot ulcers and extend ulcer-free days in remission Adherence to guideline recommended medical therapies in type 2 diabetic patients with chronic critical limb ischemia The association of ulceration of the foot with cardiovascular and all-cause mortality in patients with diabetes: A meta-analysis Patients with healed diabetic foot ulcer represent a cohort at highest risk for future fatal events A systematic review and meta-analysis of glycemic control for the prevention of diabetic foot syndrome National Evidence Based Guideline for BloodGlucose Control in Type 2 Diabetes Continuous glucose monitoring: A review of the technology and clinical use Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes Continuous Glucose Monitoring Versus Self-monitoring of Blood Glucose in Type 2 Diabetes Mellitus: A Systematic Review with Meta-analysis Longitudinal Analysis of Real-World Performance of an Implantable Continuous Glucose Sensor over Multiple Sensor Insertion and Removal Cycles Glycemic Outcomes in Adults With T1D Are Impacted More by Continuous Glucose Monitoring Than by Insulin Delivery Method: 3 Years of Follow-Up From the COMISAIR Study Continuous glucose monitoring: A consensus conference of the american association of clinical endocrinologists and american college of endocrinology Impact of ramipril in patients with evidence of clinical or subclinical peripheral arterial disease Cohort Study Examining the Association Between Blood Pressure and Cardiovascular Events in Patients With Peripheral Artery Disease Validation and Acceptability of a Cuffless Wrist-Worn Wearable Blood Pressure Monitoring Device Among Users and Health Care Professionals: Mixed Methods Study Accuracy testing of a new optical device for noninvasive estimation of systolic and diastolic blood pressure compared to intra-arterial measurements Accuracy of 24-hour ambulatory blood pressure monitoring by a novel cuffless device in clinical practice Low-Density Lipoprotein Cholesterol 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   key: cord-260713-wxfc1aaz authors: Kyle Jacques, Rose; Renza, Scibilia title: The COVID19 Pandemic – Perspectives from People Living with Diabetes date: 2020-07-22 journal: Diabetes Res Clin Pract DOI: 10.1016/j.diabres.2020.108343 sha: doc_id: 260713 cord_uid: wxfc1aaz During the unprecedented times of the COVID 19 pandemic, the lives of people with diabetes have been severely impacted. This article discusses the extent of this impact presenting the obstacles and challenges from the perspective of the patient, including specifics of practical day-to-day diabetes self-management routines. Since the COVID19 outbreak, certain psychosocial factors have been amplified due to the manner in which mainstream media and policy makers have carelessly emphasized the vulnerability of people with diabetes. The authors discuss the increased importance of support networks due to people living in isolation and quarantine. A new layer of complexity has been added to the already difficult task of managing one's diabetes and it has increased anxiety and stress levels. Guidelines and tips for people living with diabetes are discussed based on the authors' personal experiences as well as those of the diabetes associations they work with. Living with diabetes is complex and can be overwhelming. Add a global pandemic to the already monumental expectations placed on us to live healthily and maintain glucose levels in range, and it's not surprising that many people with diabetes are finding these trying times especially difficult. Impact of the Pandemic COVID-19 has exacerbated many factors involved in diabetes care and increased stress. Uncertainty around the new virus is frightening, and many people have the additional worry of loss of income 1 . The pandemic has severely disrupted routine diabetes self-management, including: The COVID19 Pandemic -Perspectives from People Living with Diabetes 2 -Food -Scarcity of healthy foods, as well as having to change diets, makes consistent diabetes management challenging. Certain products are not available. Many restaurants and stores have closed or changed their hours. -Medicine -Going to the pharmacy or seeing your doctor has become more difficult, and some people have reported problems when trying to refill prescriptions. Due to the risk of exposure to the virus, people are concerned about attending appointments, opting for telehealth/telemedicine when possible. -Physical Activity -There are obstacles to maintaining exercise, an essential element in diabetes therapy. Space is limited in our homes, parks and gyms are closed and many people face restrictions to leaving the house. Diabetes management is not only about glucose numbers. It is also about emotional well-being and mental health 2 . During the pandemic, many people with diabetes have felt more anxious, even scared, about situations out of their control. While going into lockdown keeps us safe, it also has meant that our social circles, critical for support, have shrunk. Not knowing how or when this will end can increase anxiety levels. As has been widely reported, the elderly and people with chronic health conditions, such as diabetes, are considered especially vulnerable to complications of COVID-19 3 . The dismissive and insensitive manner in which this has been repeated by the media and policy makers has been upsetting for many of us. We feel 'disposable'. In addition to this constant reminder of our vulnerability are the often-unwelcome comments from the general community about how we should manage our diabetes. Although frequently well-intentioned, this 'advice' creates enormous pressure, and adds to the already considerable social stigma we face 4 . These comments rarely help and instead make us feel that we are being judged. Support from our peers is particularly important during these unprecedented times. Most often, it is those with first-hand diabetes experience who understand how difficult it is to achieve in-range glucose levels, and how COVID-19 is impacting us. Lifestyle changes, many Rarely do two individuals react the exact same way to the exact same factor and there are many variables to consider 6 . People with diabetes try to balance everything simultaneously while using glucose monitoring technology as a guide. Often, it is a nonstop, all-consuming job which can be overwhelming enough without facing a pandemic. -Keep in touch with your healthcare team, especially for urgent care. Other medical problems don't stop during COVID-19, so it's important to seek help when you feel something is not right. An important example is keeping alert for signs of diabetic ketoacidosis. -Do the best with the situation around you. In certain areas, particularly those with high population density, social distancing/PPE guidelines cannot be followed all the time. If proper infrastructure is not in place, for example, in factories, markets, schools, hospitals, or on public transport, families of people with diabetes should take as many precautions as possible. We understand that culture and society will not change overnight, but unfortunately COVID-19 won't wait so it is important to address these risks as best as you can. -Be safe. Wash hands frequently, maintain physical distance, wear personal protective equipment such as masks, and avoid large gatherings. -Whether you receive your news via television, radio, or internet/social media, if the constant stream is making you anxious, consider taking a break! It can be exhausting to hear about matters beyond our control day-after-day. Rely on trusted sources of information, such as local diabetes organizations and the WHO. At a time when there is so much uncertainty, added stress in our daily lives is to be expected. Since diabetes doesn't allow us to take a break, it's important to adopt a methodical approach to reducing risks where possible, keeping in mind that we all need support from time to time. Together we are stronger, even with an extra few meters of space between us! Conflict of interest: The authors declare no conflict of interest. Funding: The authors received no funding from an external source. Tracking the impact of COVID-19 on the diabetes community in the United States Psychosocial Care for People With Diabetes: A Position Statement of the ADA. Diabetes Care COVID-19 and Diabetes: Knowledge in Progress I call it the blame and shame disease': a qualitative study about perceptions of social stigma surrounding type 2 diabetes Diabetes Management in Primary Care 


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   key: cord-263908-4ti8l2ea authors: Gupta, Ritesh; Hussain, Akhtar; Misra, Anoop title: Diabetes and COVID-19: evidence, current status and unanswered research questions date: 2020-05-13 journal: Eur J Clin Nutr DOI: 10.1038/s41430-020-0652-1 sha: doc_id: 263908 cord_uid: 4ti8l2ea Patients with diabetes who get coronavirus disease 2019 (COVID-19) are at risk of a severe disease course and mortality. Several factors especially the impaired immune response, heightened inflammatory response and hypercoagulable state contribute to the increased disease severity. However, there are many contentious issues about which the evidence is rather limited. There are some theoretical concerns about the effects of different anti-hyperglycaemic drugs. Similarly, despite the recognition of angiotensin converting enzyme 2 (ACE2) as the receptor for severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), and the role of ACE2 in lung injury; there are conflicting results with the use of angiotensin converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARB) in these patients. Management of patients with diabetes in times of restrictions on mobility poses some challenges and novel approaches like telemedicine can be useful. There is a need to further study the natural course of COVID-19 in patients with diabetes and to understand the individual, regional and ethnic variations in disease prevalence and course. The high prevalence of diabetes globally makes it a frequent comorbidity in patients with coronavirus-associated disease 2019 . Though diabetes increases the risk of infection in general, most studies have reported prevalence of diabetes almost similar to that in general population in patients with COVID-19. A meta-analysis of eight trials in China showed that diabetes was present in 8% of 46,248 patients with COVID-19 [1] . Understandably, prevalence of diabetes in patients with COVID-19 varies by region, age and ethnicity. It is not known whether patients with diabetes with well-controlled blood glucose levels have an increased risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). Patients with diabetes who develop COVID-19 have been seen to have a worse prognosis and increased mortality in most studies. In 201 Chinese patients with diabetes a hazard ratio of 2.34 (95% CI, 1.35-4.05; p = 0.002) for acute respiratory distress syndrome (ARDS) [2] has been reported. Further, meta-analysis of nine studies from China (n = 1936) showed a significant correlation between severity of COVID-19 and diabetes (OR, 2.67, 95% CI; 1.91-3.74; p < 0.01) [3] . Similarly, case fatality rate was 7.3% in patients with diabetes as opposed to 2.3% in those without diabetes in a report of 44,672 patients of COVID-19 by Chinese Centre for Disease Control [4] . A recent study in 1122 patients with COVID-19 in 88 centres across the USA found diabetes to be associated with more than fourfold increase in mortality [5] . How diabetes increases severity of COVID-19 is unclear, though several factors may be responsible (Table 1) . Poor glycaemic control impairs several aspects of the innate and adaptive immune response to viral infections and to the potential secondary bacterial infection in the lungs [6, 7] . Defects in immunity namely inappropriate T-cell action, impaired natural killer cell activity and defects in complement action could reduce viral clearance [8] . Interestingly, ARDS in patients with COVID-19 is driven by severe hypoxaemia despite relatively well-preserved lung mechanics. Pre-existing proinflammatory state could accentuate the cytokine storm, which is believed to be responsible for ARDS as well as multi-organ dysfunction in COVID-19 [9] . In this context, it is important to note that there is strong association between type 2 diabetes, obesity and abnormal secretion of adipokines and cytokines like TNF-alfa and interferon, which may further impair immunity and predispose to severe infection [10] . Further, diabetes is associated with increased plasminogen levels which has been postulated to increase the virulence of SARS CoV-2 [11] . Presence of these inflammation and prothrombotic factors has been shown in a study in 174 patients hospitalised with COVID-19 in Wuhan, China; significantly higher serum levels of interleukein 6, erythrocyte sedimentation rate, Creactive protein, ferritin, fibrinogen and D-dimer were reported in patients with diabetes compared with those without diabetes [12] . Increased viral replication in diabetes may also due to an increase in furin, which is a type-1 membranebound protease involved in the entry of coronaviruses into the cell [13] . In addition, pre-existing comorbidities associated with diabetes like hypertension, coronary artery disease and chronic kidney disease further worsen the prognosis. Lastly, hypoglycaemia which could occur during treatment of diabetes may additionally worsen the clinical outcomes. In this respect role of angiotensin converting enzyme 2 (ACE2) receptor in pathogenesis of COVID-19 in patients with diabetes is intriguing. SARS CoV-2 enters the cell by binding to ACE2, a process which involves many steps and several enzymes and proteins [14] . There is experimental evidence for downregulation of ACE2 in diabetes [15] , which may predispose to more severe lung injury. On the other hand, ACE2 is a receptor for SARS CoV-2 and this downregulation might reduce the entry of virus into cells. These issues are further discussed below in context of use of anti-hyperglycemic and anti-hypertensive drugs. The precise effect of treatment with various oral antihyperglycaemic agents on the severity of COVID-19 is not known, though there are some theoretical considerations. Metformin has shown modest benefits in lower respiratory tract infections and pulmonary tuberculosis [16] , though gastrointestinal tolerability in sick patients is of concern. Thiazolidinediones have been shown to increase ACE2 levels [17] . However, propensity of thiazolidinediones to cause fluid retention and the risk of congestive heart failure in COVID-19 would make these agents unfavourable for treatment. Glucagon-like peptide-1 agonists have has been shown to increase ACE2 and increase surfactant in experimental animals [18] . Practical significance of changes in ACE2 levels with use of thiazolidinediones and glucagon-like peptide-1 agonists is not known. Sulfonylureas are effective, but the risk of hypoglycaemia especially in the setting of irregular meals might preclude their use. Nevertheless, sulfonylureas can be considered whenever blood glucose monitoring is possible. There is some data regarding use of dipeptidyl peptidase 4 (DPP4) inhibitors from previous viral epidemics. DPP4 is the prime receptor for Middle East respiratory syndrome coronavirus responsible for its entry into cell [19] . Hence the possibility of DPP4 facilitating the entry of SARS CoV-2 into the cell cannot be ruled out. In that context, it is an interesting postulation that widespread use of DPP4 inhibitors in India and many other countries might be protecting individuals with diabetes from this infection. On the other hand, DPP4 inhibitors can potentially interfere with immune response which may be harmful, but clinical data from DPP4 inhibitors has shown that this is generally not the case [20] . There is increasing use of sodium glucose cotransporter 2 (SGLT-2) inhibitors worldwide and in India. Interestingly, SGLT-2 inhibitors could also activate ACE2 indirectly especially if used along with ACE inhibitors [21] . There is a hypothetical possibility of SGLT-2 inhibitors reducing lactate production because of reduction in oxygen demand of tissues, which could reduce viral entry by raising cytosolic pH [22] . Further, caution about dehydration and the possibility of euglycaemic ketoacidosis need to be observed when using SGLT-2 inhibitors in sick patients with COVID-19. Insulin has also been shown to increase ACE2 expression by attenuating the effect of a disintegrin and metalloprotease (ADAM-17) [23] . Practical relevance of these findings is not known at present. In any case, insulin Thus, it appears safe to continue the usual antihyperglycemic medications in most patients who have mild infection, good general condition and normal oral intake. However, SGLT-2 inhibitors might need discontinuation due to the risk of dehydration and euglycaemic ketoacidosis. Metformin may also need to be stopped if there is vomiting or poor oral intake. Doses of other antihyperglyacemic drugs like sulfonylureas and insulin may have to be altered depending upon the blood glucose levels. Hospitalised patients especially those requiring intensive care would need insulin for glycaemic control. Angiotensin converting enzyme (ACE) inhibitors/ angiotensin receptor blockers (ARB) These are commonly used drugs in patients with diabetes, especially in those with hypertension and kidney dysfunction. There have been a lot of literature and debate whether these drugs could benefit or harm patients having COVID-19 infection. This issue is discussed below. Scientific experimental data that support potential harm duet to ACE inhibitors/ARB in COVID-19 There has been a lot of interest in ACE inhibitors and ARBs following the identification of ACE2 as the receptor for SARS CoV-2. ACE inhibitors and ARBs increase the levels of ACE2 by inhibiting the conversion of angiotensin 1 to angiotensin 2. Increased ACE2 expression could theoretically increase viral binding and entry into cell, though there is no clinical evidence to support this otherwise attractive hypothesis. Reduced angiotensin 2 as a result of ACE inhibition and increased angiotensin 1-7 as a result of increased activity of ACE2 could reduce the cytosolic pH, which could result in more favourable environment for viral endocytosis [24] . Also, angiotensin 1-7 has been shown to increase sympathetic activity by acting on Mas receptors in the brainstem, which could contribute to cardiovascular morbidity observed in these patients [25] . However, most of these concerns are hypothetical with minimal evidence. Scientific experimental data that support benefit due to ACE inhibitors/ARB in COVID-19 Increased ACE2 might not result in increased viral entry because of the limited availability of the serine protease TMPRSS2, which is required for viral binding [20] . Increased ACE2 and consequently angiotensin 1-7 have vasodilatory and antifibrotic effects and have been shown to be protective against lung injury in animals [26] . Treatment with ARBs was reported to reduce mortality in Ebola virus infection [27] . Previously, a small study in ten patients with ARDS showed that recombinant ACE2 was well tolerated and led to an increase in angiotensin (1-7) levels [28] . (1) There are no controlled studies on the use of ACE inhibitors and ARBs in patients with COVID-19. (2) The clinical evidence is inconclusive. While one study in China did not find any association of ACE inhibitor use with severity of disease, there was an increased mortality in patients with COVID-19 receiving ACE inhibitors and ARBs in another study [29, 30] . One study in the USA did not find any significant difference in mortality in patients who received ACE inhibitors and ARBs and those who did not [31] . In this subject situation is far from clear and there are too many unknown factors, which might be operative in the interaction between ACE2, diabetes, ACE inhibitors/ARBs and lung injury. The lack of evidence for either benefit or harm has prompted European Society of Cardiology Council on Hypertension, European Society of Hypertension and American Heart Association to advise continuing with ACE inhibitors and ARBs in case a patient develops COVID-19 [35] . A clinical trial is underway to study the ARB losartan and recombinant human ACE2 in patients with COVID-19. There have been several commentaries on the relationship between diabetes and COVID-19 [36] . However, several unanswered questions remain, about which the knowledge and information is limited. Clearly, further research could lead to important insights ( Table 2) . Some of these are discussed below. (1) What is the natural history of COVID-19 in patients with diabetes? The natural course of the disease after infection of patients with diabetes with SARS CoV-2 has not been documented well. For example, we don't know if the incubation period is different in people with diabetes. It is also possible those patients of diabetes who are young, have short duration of diabetes, and well controlled may have less severe COVID-19 infection. There is a possibility of reduced viral clearance in diabetes as has been reported in patients who are on corticosteroids [37] . This could have public health implications as the patients with diabetes could remain infectious for a longer period than those without diabetes. a. Chloroquine has also been licensed for use in India for patients with type 2 diabetes. Although the efficacy of chloroquine is not proven; it has been used in patients with COVID-19 [38] . Chloroquine has a weak anti-hyperglycaemic effect and there is a theoretical risk of hypoglycaemia when used in combination with other antihyperglycaemic drugs. b. Corticosteroids, though neither effective nor recommended, are frequently used in ARDS and sepsis and would worsen glycemic levels. (3) COVID-19 and pancreatic beta cells: there is significant expression of ACE2 receptors in pancreatic islets and hyperglycaemia lasting up to 3 years has been reported in patients with SARS [39] . Direct injury to beta cells is a possibility and patients recovering from COVID-19 might need major changes in anti-hyperglycaemic regimen. Recently, new-onset diabetes has been reported in patients with COVID-19 [11] . (4) Suboptimal lifestyle measures and other issues during lockdown: a. There are restrictions on movement of people and 'lockdowns' in several parts of the world in order to contain the pandemic. This poses some challenges in the evaluation and treatment of patients with diabetes. There are limited opportunities for exercise as regular walks and visits to gyms or swimming pools are not possible. Dietary irregularity could occur because of staying at home. b. There is considerable mental stress because of the unpredictability of the disease as well as social immobility as brought out in an excellent study in healthy people in China at the time when there was a huge burden of COVID-19 there [40] . c. Patients may find it difficult to procure healthy foods, medicines, insulin, needles and glucose strips etc. because of partial or complete lockdowns. The problem becomes more pronounced with elderly, poor and disadvantaged sections of society. d. There could be underreporting of symptoms because of the perceived need to avoid visiting hospitals. All these factors could cause glucose dysregulation and could predispose patients to complications like infections, hyperosmolar coma, ketoacidosis and even acute cardiac events. A prediction model of the effect of lockdown in India on blood glucose showed a 3.6% increase in HbA1c at the end of 45 days of lockdown and future increase in diabetes-related complications [41] . (1) Are people with well-controlled diabetes at higher risk of getting COVID-19 infection than non-diabetic individuals? (2) Is there any effect of obesity on the severity of COVID-19 in people with diabetes? (3) Is there any specific diet or supplement which could help patients of diabetes and COVID-19? (4) What is the role of renin angiotensin aldosterone system (RAAS) and inhibitors of RAAS in determining the predisposition to COVID-19 and its severity? (5) Use of remote education and advice: Telemedicine (also emails, texts) can be very helpful in these times to impart education and has been shown to improve glycaemia. Telemedicine guidelines for physicians in India have been published [42] . Patients need to be educated about the need to visit the hospital urgently in emergency situations like vomiting, drowsiness, shortness of breath, chest pain, weakness of limbs, altered sensorium, etc [43] . (6) COVID-19 testing for all patients with diabetes? Given the increased severity of COVID-19 in patients with diabetes, a case could be made for testing of all people with diabetes for the presence of disease. That would be a humongous task considering the high prevalence of diabetes. High-risk groups like those with high HbA1c, those with comorbidities, long duration of diabetes or elderly could be chosen for testing, however, utility of this approach remains to be proven, There are frequent false negative tests and repeated testing may be required in asymptomatic individuals. Since there is no treatment currently recommended for asymptomatic people, therefore apart from isolating them, detecting these patients might not prove meaningful clinically. (7) Ethnic variations in severity of COVI19 in patients with diabetes? In the United States, the disease has caused disproportionately more fatalities in Blacks and Asians compared with Whites [44] . South Asia, Africa and Korea have seen much lower mortality than rest of the world. Whether it is because of the different approaches topublic health measures, innate immunity or due to some ethnicity-specific variability in response to viral infection, or availability of good medical resources, remains to be studied. Interactions between ethnicity, diabetes and severity of COVID-19 will be of interest, considering the racial disparities in the prevalence of diabetes. According to a recent report, prevalence of COVID-19 and mortality due to the disease correlated significantly with frequency of D allele in ACE gene [45] . Such polymorphisms in ACE gene as well as several other genes involved in the pathophysiology of COVID-19 might be responsible for individual and ethnic variations in disease course. (8) Benefits of lockdown? There could be some positive effects of the social restrictions. a. Patients have more time for self-care and could pay more attention to diet and exercise if motivated. b. Some people have stopped or reduced alcohol and smoking because of non-availability. c. There has been significant fall in air pollution as a result of reduced industrial and vehicular emissions [46] . Increase in blood glucose has been reported with short-term rise in pm 10 (particulate matter <10 microns in diameter) and glycaemic improvement could occur with the fall in pollution [47] . In view of the issues highlighted above, it is important to recognise the importance of diabetes as a vital comorbidity in patients with COVID-19. There are several contentious issues and the ongoing research will hopefully shed more light on the behaviour of COVID-19 in patients with diabetes. Author contributions RG and AM planned the outline of manuscript. RG reviewed the literature and wrote the manuscript. RG, AM and AH edited the manuscript. Conflict of interest The authors declare that they have no conflict of interest. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 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Ambientair pollution and diabetes: a systematic review and meta-analysis 


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   key: cord-264295-7ojvhwb0 authors: Maddaloni, Ernesto; D’Onofrio, Luca; Alessandri, Francesco; Mignogna, Carmen; Leto, Gaetano; Pascarella, Giuseppe; Mezzaroma, Ivano; Lichtner, Miriam; Pozzilli, Paolo; Agrò, Felice Eugenio; Rocco, Monica; Pugliese, Francesco; Lenzi, Andrea; Holman, Rury R.; Mastroianni, Claudio Maria; Buzzetti, Raffaella title: Cardiometabolic multimorbidity is associated with a worse Covid-19 prognosis than individual cardiometabolic risk factors: a multicentre retrospective study (CoViDiab II) date: 2020-10-01 journal: Cardiovasc Diabetol DOI: 10.1186/s12933-020-01140-2 sha: doc_id: 264295 cord_uid: 7ojvhwb0 BACKGROUND: Cardiometabolic disorders may worsen Covid-19 outcomes. We investigated features and Covid-19 outcomes for patients with or without diabetes, and with or without cardiometabolic multimorbidity. METHODS: We collected and compared data retrospectively from patients hospitalized for Covid-19 with and without diabetes, and with and without cardiometabolic multimorbidity (defined as ≥ two of three risk factors of diabetes, hypertension or dyslipidaemia). Multivariate logistic regression was used to assess the risk of the primary composite outcome (any of mechanical ventilation, admission to an intensive care unit [ICU] or death) in patients with diabetes and in those with cardiometabolic multimorbidity, adjusting for confounders. RESULTS: Of 354 patients enrolled, those with diabetes (n = 81), compared with those without diabetes (n = 273), had characteristics associated with the primary composite outcome that included older age, higher prevalence of hypertension and chronic obstructive pulmonary disease (COPD), higher levels of inflammatory markers and a lower PaO2/FIO2 ratio. The risk of the primary composite outcome in the 277 patients who completed the study as of May 15(th), 2020, was higher in those with diabetes (Adjusted Odds Ratio ((adj)OR) 2.04, 95%CI 1.12–3.73, p = 0.020), hypertension ((adj)OR 2.31, 95%CI: 1.37–3.92, p = 0.002) and COPD ((adj)OR 2.67, 95%CI 1.23–5.80, p = 0.013). Patients with cardiometabolic multimorbidity were at higher risk compared to patients with no cardiometabolic conditions ((adj)OR 3.19 95%CI 1.61–6.34, p = 0.001). The risk for patients with a single cardiometabolic risk factor did not differ with that for patients with no cardiometabolic risk factors ((adj)OR 1.66, 0.90–3.06, (adj)p = 0.10). CONCLUSIONS: Patients with diabetes hospitalized for Covid-19 present with high-risk features. They are at increased risk of adverse outcomes, likely because diabetes clusters with other cardiometabolic conditions. being frequent comorbidities in patients with Covid-19 who require intensive care or die [6, 7] . Type 2 diabetes, in particular, might hypothetically impact on all of the different aspects of SARS-CoV-2 infection, from the contagion to the clinical presentation and to disease severity [8] . Further, in-hospital hyperglycaemia has been associated with worse Covid-19 outcomes [9] , being a negative prognostic factor at hospital admission in both patients with and without diabetes [10] . In addition, regardless of diabetes diagnosis, hyperglycaemia reduced the efficacy of treatment with Tocilizumab in patients affected by Covid-19 [11] . On the other hand, a recent report from Wuhan failed to show an independent association of type 2 diabetes with Covid-19 mortality after adjustment for other cardiovascular conditions [12] . Notably, most cardiometabolic disorders share a common pathogenic soil, often cluster together, and might reflect the same intermediate pathways that favour Covid-19 progression [13] [14] [15] . Therefore, assessing the possible association of type 2 diabetes with Covid-19 outcomes based on individual cardiometabolic disorders may be subject to a collider bias, leading to distorted results [16, 17] . This makes it difficult to disentangle independent associations Covid-19 may have with single components of cardiometabolic multimorbidity, defined here as a group of main metabolic disorders that increase the risk of cardiovascular events, such as diabetes, hypertension and dyslipidaemia. Nevertheless, most studies investigating diabetes as a risk factor for Covid-19 progression searched for independent associations, leading to conflicting conclusions [12, [18] [19] [20] . We, instead, hypothesized that people with diabetes may differ from those without diabetes in their clinical presentation, course and prognosis of Covid-19 due to the propensity of diabetes to cluster with other cardiometabolic risk factors, such as hypertension and/or dyslipidaemia, which contribute to the increased pro-inflammatory and hypercoagulable states of people with diabetes. Furthermore, most studies published to date on this topic come from Asian countries, with few data available from Western countries where differences in ethnic groups and healthcare systems may lead to different associations [21, 22] . Overall, there is an urgent need for additional data to clarify the relationships between diabetes, cardiometabolic multimorbidity and Covid-19 [18] which could provide significant insights of global health interest to help tackle this deadly pandemic in a large group of atrisk individuals. We aimed to describe in detail, using opportunistic data collected retrospectively, the clinical and biochemical features of patients with and without diabetes hospitalized for Covid-19 in four academic hospitals in the Lazio region, Italy, to evaluate their outcomes, and to evaluate the impact of cardiometabolic multimorbidity. The Covid-19 & Diabetes (CoViDiab) study is a multicenter observational study which collected data retrospectively from medical charts of patients hospitalized for Covid-19 from March 1 st to May 15 th , 2020 in four academic hospitals located in the Lazio region of Italy: Umberto I "Policlinico" General hospital and Sant' Andrea hospital, Sapienza University of Rome; Santa Maria Goretti hospital, Polo Pontino of Sapienza University in Latina; Campus Bio-Medico University hospital in Rome [23] . Patients eligible for inclusion were aged ≥ 18 years old with a diagnosis of Covid-19 confirmed by at least one real-time polymerase chain reaction assay, in accordance with the protocol established by the World Health Organisation [24] . After exclusion of 19 patients with unknown diabetes status, baseline data for 354 patients and clinical outcomes for 277 patients up to May 15 th , 2020 were available for inclusion in this analysis. The CoViDiab primary aim was to evaluate whether patients with diabetes, compared with those without diabetes, were at increased risk of adverse Covid-19 outcomes, independent of age and sex. The composite primary outcome was defined as any of mechanical ventilation, admission to an intensive care unit (ICU), or death. Pre-specified secondary endpoints included a composite outcome of ICU admission or death and allcause mortality (ACM). In this study, we did not seek to test whether diabetes as a risk factor for Covid-19 progression is independent of hypertension and dyslipidaemia, which may be considered as coexisting components of a single cardiometabolic disorder (or syndrome). Instead, our secondary aim (if diabetes was confirmed to be associated with an increased risk of the primary composite outcome) was to evaluate whether cardiometabolic multimorbidity (defined as ≥ 2 of three risk factors of diabetes, hypertension and dyslipidaemia) may be considered as a risk factor that differs from a single cardiometabolic condition. Accordingly, patients were stratified into three mutually exclusive cardiometabolic groups: no conditions, one condition and two or three conditions. Data collected included: demographic information (age and sex); presence of diabetes (defined as at least one random blood glucose value > 200 mg/dl, or fasting blood glucose > 126 mg/dl, or HbA 1c > 6.5%, or self-reported history of diabetes with ongoing anti-diabetes therapy), type of diabetes (type 1, type 2, other); smoking habits (never, ex, current); prior history of hypertension, dyslipidemia, chronic obstructive pulmonary disease (COPD), heart failure, cardiovascular events (myocardial infarction, percutaneous coronary intervention, coronary artery-bass graft or stroke), malignancy (any neoplasia diagnosed within the last five years or active neoplasia); presenting symptoms of SARS-CoV-2 infection (fever, cough, cold, conjunctivitis, chest pain, dyspnea, nausea, vomiting, diarrhea). Biochemical data measured at admission, where available, were: plasma glucose, serum creatinine, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), full blood count, lactate dehydrogenase, fibrinogen, D-dimer and blood gas analysis. Body mass index (BMI) was calculated for the 169 patients with height and weight data available. Usual care medications at admission were ascertained from those reported by the inpatient-accepting physician. Diabetes usual care medications were also retrieved from the web-based reimbursement system of Lazio region (Web-Care Lazio), as categorized by this system: euglycaemic agents (EuGlA: metformin, dipeptidyl peptidase 4 inhibitors [DPP4i], glucagon-like peptide 1 receptor agonists [GLP-1RA], sodium-glucose co-transporter 2 inhibitors [SGLT2i] and/or pioglitazone); oral hypoglycaemic agents (OHA: sulfonylureas or glinides); basal insulin (alone or in combination with EuGlA or OHA); multiple daily insulin injections (MDI: ≥ 3 insulin injections per day). The WebCare Lazio system was also used to confirm a self-reported history of diabetes. Continuous variables are presented as medians [25th-75th percentile]. Categorical variables are presented as number and percentages, calculated on the data available. We made no assumptions regarding missing data. Kruskal-Wallis, Chi-squared and Fisher exact tests were used for comparisons between groups, as appropriate. We estimated that at least 200 patients completing the study would be required to provide 80% power to detect a 2.5-fold higher incidence of the primary composite outcome in patients with diabetes hospitalized for Covid-19, compared with those without diabetes, using a one-sided alpha-level of 0.05 and allowing for adjustment of sex and age. Logistic regression models adjusted for age and sex were used to investigate associations of the primary and secondary outcomes with diabetes, and with other risk factors explored in the study, namely hypertension, dyslipidemia, COPD, heart failure, previous cardiovascular events, malignancy and smoking status (never vs. ever). The secondary aim of the study (association of cardiometabolic multimorbidity with the primary composite outcome) was also explored using a logistic regression model adjusted for age, sex and risk factors (other than hypertension, diabetes and dyslipidemia) that were univariately associated (p < 0.1) with the outcome after correction for age and sex. The Wald test was used to test equality of the regression coefficients between cardiometabolic groups. Stata/IC 12.1 software was used for data analysis and Prism 8.4 Software for graphical presentations. CoViDiab complies with the principle of the Helsinki Declaration and was approved by the Ethical Committee of Umberto I "Policlinico" General hospital. Because of the study's retrospective design, informed consent was waived for patients who had been discharged, could not be contacted, or died. The privacy and anonymity of the data collected was guaranteed in accordance with current regulations. Presenting characteristics for all 354 patients are listed in Table 1 . Patients with diabetes, compared with those without diabetes, were older (age ≥ 70 years: 64.2% vs. 33.0%, p < 0.001) but with a similar sex distribution. They also presented with higher rates of hypertension (66.7% vs. 46.1%, p = 0.001), dyslipidemia (37.2% vs. 18.0%, p < 0.001), prior cardiovascular events (16.0% vs. 7.7%, p = 0.026), heart failure (12.8% vs. 4.1%, p = 0.005) and COPD (21.2% vs. 10.0%, p = 0.008). No differences in smoking habits or malignancy rate were found. BMI did not differ between patients with and without diabetes. At No differences were observed in the frequencies of SARS-CoV-2 infection presenting symptoms between patients with and without diabetes (Additional file 1: Table S1 ). Continuous variables are presented as median [25th, 75th percentile]; categorical variables are presented as number (percentage) # p-value for difference in never, ex and current mokers EuGlA, euglycemic agents (metformin, dipeptidyl peptidase 4 inhibitors, glucagon-like peptide 1 receptor agonists, sodium-glucose co-transporter 2 inhibitors and/ or pioglitazone); OHA, oral hypoglycaemic agents (sulfonylureas or glinides); MDI, multiple daily insulin injections; RAAS, renin-angiotensin-aldosterone system; ACEi, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blocker; CV, cardiovascular; COPD, chronic obstructive pulmonary disease; ESR, erythrocytes The primary composite outcome occurred in 128 (46.2%) of the 277 patients who completed the study (discharged alive or experiencing at least one component of the primary composite outcome). Differences in clinical features between those experiencing the primary composite outcome and those discharged alive (n = 149), mostly mirrored the differences seen between patients with and without diabetes ( Table 1) . Those with, compared with those without the primary composite outcome, were more often > 70 years old (p < 0.001) and more likely to have hypertension (p < 0.001), dyslipidemia (p = 0.047), heart failure (0.038) or COPD (p = 0.001). There was no difference in prior history of CV events between groups but those with the primary composite outcome were less often current smokers than never smokers (0.9% vs. 7.8%, p = 0.032). BMI in the 150 patients with BMI data and complete follow-up, was higher in those with the primary composite outcome compared with those discharged alive not requiring neither ICU admission or mechanical ventilation ( Differences in biochemical features between patients with, compared with those without the primary composite outcome, also paralleled the differences seen between patients with and without diabetes (Table 1) . Those experiencing the primary composite outcome had higher plasma glucose (p < 0.001), serum creatinine (p = 0.016), CRP (p < 0.001), white blood cell count (p < 0.001), neutrophil count (p < 0.001) and venous lactate (p = 0.002), and a lower PaO 2 /FIO 2 ratio (p < 0.001). They also had higher lactate dehydrogenase (p < 0.001) and D-dimer (p = 0.006) concentrations, but had a lower lymphocyte count (p = 0.015). Frequencies of SARS-CoV-2 infection presenting symptoms were similar among patients with, compared with those without the primary composite outcome, apart from dyspnea which was more frequent among those experiencing the primary composite outcome (66.1% vs. 40.9%, p < 0.001) (Additional file 1: Table S1 ). Age and sex adjusted regression models confirmed that Covid-19 patients with the primary composite outcome were more likely to have diabetes (adjusted odds ratio [ adj OR] 2.04, 95% confidence interval [CI] 1.12-3.73, p = 0.020), hypertension ( adj OR 2.31, 95%CI 1.37-3.92, p = 0.002) or COPD ( adj OR 2.67, 95%CI 1.23-5.80, p = 0.013), while the associations with dyslipidemia and heart failure were lost (Fig. 1a) . Therapies for diabetes at admission did not differ between patients with diabetes in whom the primary composite outcome did or did not occur (Table 1) . Similarly, there was no difference in the use of angiotensinconverting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARB) between patients who did or did not experience the primary outcome (18.0% vs 16.1%, p = 0.55 and 14.8% vs 13.4%, p = 0.60, respectively). Of the 277 patients completing the study, 100 (36.1%) did not have diabetes, hypertension or dyslipidaemia, 96 (34.7%) had just one of these risk factors (16 with diabetes, 70 with hypertension, 10 with dyslipidaemia), and 81 (29.2%) had ≥ two of these risk factors meeting our study definition of cardiometabolic multimorbidity. The proportion of patients > 70 years old (p < 0.001), with a prior cardiovascular event (p < 0.001), heart failure (p = 0.007) or COPD (p = 0.002), and higher concentrations of plasma glucose (p < 0.001), creatinine (p = 0.010), CRP (p = 0.043) and venous lactate (p < 0.001) increased with increasing numbers of cardiometabolic conditions, and with a decreasing PaO 2 /FIO 2 ratio (p = 0.002) ( Table 2) . The proportion of patients experiencing the composite primary outcome increased with increasing numbers of cardiometabolic risk factors (Fig. 2) , independently of age, sex and COPD ( adj p = 0.004). The risk of the primary composite outcome in patients with cardiometabolic multimorbidity, compared with those with no cardiometabolic risk factors, was higher ( adj OR [95% CI] 3.19 [1.61-6.34], adj p = 0.001). They also were at higher risk when compared with patients with a single cardiometabolic risk factor ( adj OR 1.92, 1.02-3.64, adj p = 0.045). The risk for patients with a single cardiometabolic risk factor, however, did not differ with that for those with no cardiometabolic risk factors ( adj OR 1.66, 0.90-3.06, adj p = 0.10). Analyses examining the secondary outcomes of ICU admission or death, and ACM alone, were performed for patients who were admitted to ICU, died or were discharged alive without ICU admission (n = 259), and for the those who died or were discharged alive at study end (n = 228). ICU admission or death occurred in 77 (29.7%) sedimentation rate; CRP, c-reactive protein; PaO2, arterial pO2; FIO2, fraction of inspired oxygen Body mass index data were available for *120, **49, ***55 and ****95 patients Smoking data were available for ^244, ^^73, ^^^129 and ^^^^114 patients Anti-diabetes therapy data were available for 58 of the 63 patients with diabetes who completed the study Fig. 1 Proportion of patients experiencing the primary composite outcome (a), and the secondary outcomes of ICU admission or death (b), or death (c) among patients with or without different comorbidities. Age and sex adjusted odds ratios (OR) with 95% confidence intervals (CI) for those with, compared with those without, each comorbidity are reported. Error bars represent 95% confidence intervals in the former, and 29 (12.7%) of the latter died. After adjustment for age and sex, diabetes was not associated with either of these secondary outcomes, whereas a prior history of COPD or heart failure was (Fig. 1b, c and Additional file 1: Table S2 ). Our study shows that the characteristics associated with worse Covid-19 outcomes are found more frequently in patients with diabetes than in those without diabetes. These include older age, higher prevalence of chronic comorbidities such as hypertension or COPD, higher levels of inflammatory markers, and a lower PaO 2 /FIO 2 ratio. Accordingly, the risk of progression towards mechanical ventilation, ICU admission or death was significantly higher among patients with diabetes than in those without, independent of age and sex. As we expected, only a minority of patients with diabetes (25.4%) had neither hypertension nor dyslipidemia, supporting our choice not to consider these risk factors as independent variables. This observation suggests that findings from studies reporting diabetes is not associated with Covid-19 severity after adjustment for other cardiovascular conditions should be interpreted with caution [12] . In line with our hypothesis, patients with cardiometabolic multimorbidity had a higher risk of the primary outcome compared with patients with no or a single cardiometabolic risk factor (diabetes, hypertension or dyslipidaemia). Compared with patients with no cardiometabolic risk factors, the primary composite outcome was also higher among patients with a single risk factor, but was not significant after adjustment for age, sex and presence of COPD. Of note, while drugs targeting the incretin system or the renin-angiotensin-aldosterone system have been hypothesized to be associated with Covid-19 outcomes [25, 26] , their use did not differ between patients with or without the primary outcome. Overall our results confirm previous findings from other countries that Covid-19 patients with diabetes are more likely to require intensive care or to die, compared with Covid-19 patients without diabetes [12, 19, 20, 27] , and in addition suggest this association is driven by the presence of cardiometabolic multimorbidity rather than by diabetes alone. In this regard, categorizing patients as having cardiometabolic multimorbidity, rather than a simply summing risk factors [15] , seems to almost completely explain the interaction between cardiometabolic disorders and Covid-19. Coexisting cardiometabolic risk factors may indeed either be the expression of a common pathogenic soil or cooperate with each other to predispose Covid-19 patients to progress towards more severe clinical scenarios. In patients presenting with diabetes but not hypertension or dyslipidemia, pathogenic pathways involved may not be sufficiently affected to impact on the clinical course of Covid-19. The observation that cardiometabolic multimorbidity worsens Covid-19 is of clinical relevance, highlighting the importance of tackling cardiovascular risk as a whole to improve Covid-19 outcomes. Of note, an estimation of the overall effects of the Covid-19 outbreak according to underlying conditions has also suggested that cardiovascular comorbidities, together with COPD, may be responsible for the majority of excess deaths associated with Covid-19 pandemic from both direct and indirect effects [28] . Different mechanisms may be hypothesized to explain the association of cardiometabolic health with Covid-19 outcomes. It has been suggested that Covid-19 not only affects the respiratory system but also the vasculature [29] [30] [31] [32] . Direct SARS-CoV-2 infection of endothelial cells causing endothelitis in several organs has been demonstrated in patients dying from Covid-19 [33] , suggesting Covid-19 is an infectious disease affecting endothelial function. It is worth hypothesizing therefore, that cardiometabolic multimorbidity may predispose to worse Covid-19 outcomes by weakening endothelial cells [34] , which then become more susceptible to viral infection. Additionally, the hypercoagulable and pro-inflammatory states often observed in cardiometabolic patients [35] may also contribute towards the formation of the multiple blood clots and the cytokine storm that can occur in the most severe Covid-19 cases [36, 37] . This endothelial hypothesis accords with recent data suggesting that a high amount of visceral adiposity, a common feature of cardiometabolic patients associated with chronic lowgrade inflammation, associates with worse Covid-19 outcomes [38] . While measures of visceral adiposity were not available in our study, BMI was found to be higher in patients with the primary outcome, consistent with previous reports in other populations [4, 39] . The trend we noted towards higher BMI with increasing number of cardiometabolic risk factor in the relatively low number of patients with BMI data available our population was not statistically significant. Limitations to our study include retrospective collection of data from electronic and paper records, relatively few patients with BMI data available, and incomplete followup of some patients without an endpoint who were still hospitalized at the time of this analysis. Also, we were not able to retrieve glycemic control data during hospitalization, which has been associated with worse Covid-19 outcomes [9, 20] . The small number of deaths does not allow us to make any conclusions about the non-significant association of diabetes with ACM, which was however associated with prior history of hypertension, COPD or heart failure. Finally, we were not able to estimate insulin resistance, or surrogates such as triglyceride-glucose index [40] , in our population, which is often considered the common soil for cardiometabolic conditions. Similarly, the absence of waist circumference data not allow us to identify patients with the metabolic syndrome to assess its possible impact, although the utility of this categorisation in type 2 diabetes has been increasingly questioned [41] . Unfortunately, due to the observational study design and the demanding work condition determined by the pandemic, we were unable to collect additional blood samples or to perform additional radiological investigations to test bio-markers not routinely measured in all patients, such as cardiac troponin, interleukins, or to assess visceral adiposity, all of which may be involved in the relationship between cardiometabolic multimorbidity and Covid-19 progression [38, 42, 43] . Novel studies should be performed to evaluate whether the increased risk conferred by cardiovascular multimorbidity is associated to augmented cytokine storm and to central obesity. Strengths of our study include a detailed characterization of the clinical and biochemical features of patients hospitalized for Covid-19, with and without diabetes, with good generalizability of the results thanks to the multicentre study design. Furthermore, to the best of our knowledge, this is the first study assessing Covid-19 outcomes in the context of cardiometabolic multimorbidity. Our study shows that patients with diabetes hospitalized for Covid-19 present with high-risk clinical and biochemical features and are at increased risk of mechanical ventilation, ICU admission or death, likely because diabetes frequently clusters with cardiometabolic multimorbidity. Supplementary information accompanies this paper at https ://doi. org/10.1186/s1293 3-020-01140 -2. Additional file 1: Table S1 . SARS-CoV-2 infection symptoms at hospitalization in patients with, compared with those without, diabetes and in patients experiencing the primary composite compared with those without. Table S2 . Odds ratio (OR) with [95% confidence intervals, CI] for secondary outcomes, unadjusted and adjusted for age and sex. Abbreviations: CV, cardiovascular; COPD, chronic obstructive pulmonary disease. 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A report of thromboelastography findings and other parameters of hemostasis Facing COVID-19 in the ICU: vascular dysfunction, thrombosis, and dysregulated inflammation The role of visceral adiposity in the severity of COVID-19: Highlights from a unicenter cross-sectional pilot study in Germany Letter to the Editor: Obesity as a risk factor for greater severity of COVID-19 in patients with metabolic associated fatty liver disease Triglyceride-glucose index is associated with symptomatic coronary artery disease in patients in secondary care Impact of the metabolic syndrome on macrovascular and microvascular outcomes in type 2 diabetes mellitus Cardiac Troponin for the Diagnosis and Risk-Stratification of Myocardial Injury in COVID-19: JACC Review Topic of the Week EM designed the study, analysed and interpreted data and wrote the first draft of the manuscript. LDO contributed to the design of the study, data acquisition, interpretation and manuscript writing. CM acquired data and helped in data interpretation; FA, GL, IM, ML, FEA, FP, and GP acquired data. PP, MC, AL revised the manuscript for important intellectual content. RRH contributed to data interpretation and revised the manuscript for important intellectual content. CMM contributed to the design of the study and acquisition of the data. RB was responsible for the conception of the study, contributed to study design and data interpretation and revised the manuscript critically for important intellectual content. All authors read and approved the final manuscript. The study was in part supported through the EFSD Mentorship Programme supported by AstraZeneca. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. CoViDiab complies with the principle of the Helsinki Declaration and was approved by the Ethical Committee of Umberto I "Policlinico" General hospital. Because of the study's retrospective design, informed consent was waived in cases of discharge, of impossibility of contact with patients and in case of death. The privacy and anonymity of the data collected was guaranteed in accordance with current regulations. Not applicable. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 


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   key: cord-266702-6oxtlzqo authors: Cristelo, Cecília; Azevedo, Cláudia; Moreira Marques, Joana; Nunes, Rute; Sarmento, Bruno title: SARS-CoV-2 and Diabetes: New Challenges for the Disease date: 2020-05-22 journal: Diabetes Res Clin Pract DOI: 10.1016/j.diabres.2020.108228 sha: doc_id: 266702 cord_uid: 6oxtlzqo A novel small enveloped RNA virus with the typical characteristic of the family to which it belongs, a crown, hence the name coronavirus, appeared in December 2019 in Wuhan, China, and subdued the world to its influence. The particular severity of the disease and higher mortality rates in patients with associated morbidities, including hypertension, obesity and diabetes, increases the concern over the consequences of this pandemic. In this review, the features of SARS-CoV-2 will be addressed, as well as the reasons why it poses a particular challenge to diabetic patients. We will also highlight the recent treatment strategies being explored to control this pandemic. Emerging evidence demonstrates that the correct management of diabetes in those patients infected with SARS-CoV-2 is of utmost importance for the viral disease progression, therefore, the importance of blood glucose control will also be addressed. SARS-CoV-2 shares 89% homology with bat SARS-like-CoVZXC21, 82% with human SARS-CoV and around 50% with Middle East Respiratory Syndrome coronavirus (MERS-CoV) [2] . As all the other coronaviruses, SARS-CoV-2 comprises the four structural proteins E (envelope protein), M (membrane protein), N (nucleocapsid protein) and S (spike protein), as well as eight accessory proteins [5] . The spike surface glycoprotein plays an essential role by promoting the attachment of the virus to its receptor on host cells and may determine its host tropism and transmission ability. Receptor-binding domain (RBD) of S-protein from SARS-CoV-2 shares identical 3D structure with the RBD of S-protein from SARS-CoV, as well as 76.47% amino acid sequence homology [6] . In vitro and in vivo studies showed that angiotensin-converting enzyme 2 (ACE2) is the cellular receptor for SARS-CoV virus [7, 8] . The novel SARS-CoV-2 also binds to ACE2 [2, [9] [10] [11] with 10 to 20 times higher affinity than SARS-CoV does [12] . In addition, SARS-CoV-2 employs the cellular transmembrane serine protease 2 (TMPRSS2) for S protein priming, allowing internalization and replication in the host cells [11] . ACE2 is a naturally occurring enzyme abundantly present in humans, mainly in the cell membrane of lung alveolar epithelial cells [13] [14] [15] [16] and enterocytes of the small intestine [15] , which provide as entry routes for the SARS-CoV infection and probably SARS-CoV-2. Additionally, ACE2 is also expressed by arterial and venous endothelial cells and arterial smooth muscle cells [15] , cholangiocytes [17] , testis [13, 14] , pancreas [18, 19] , in cardiovascular [13, 14, 16] , renal [13, 14, 16] , urothelial [16] , mucosal [20] and gastrointestinal tissues [16, 21] in minor extent. ACE2 is homologous to the firstly discovered ACE1, and both enzymes are part of the reninangiotensin system (RAS), which has a crucial role in regulating blood pressure, maintaining electrolyte and fluid homeostasis for its potent vasoconstrictor/vasodepressor actions [22] . RAS is an enzymatic cascade starting with the cleavage of angiotensinogen by renin to form angiotensin (Ang) I. This peptide is then further metabolized by ACE1, which removes two amino acids at the C-terminal end to form the potent vasopressor peptide Ang II [23] . Ang II levels are endogenously regulated by the ACE2, which is a membrane-bound monocarboxypeptidase that cleaves the terminal leucine and phenylalanine residues from Ang I and Ang II originating Ang 1-9 and Ang 1-7, respectively. The hexapeptide Ang 1-7 exerts a potent vasodilator, anti-fibrotic, anti-proliferation and anti-inflammatory effect via activation of its Mas receptor. Its effects counterbalance the ACE1-Ang II-ATR1 system [24] . On a similar manner, ACE1 inhibitor drugs (ACEIs) have an antihypertensive effect and substantially lower the risk of death, heart failure and stroke [25] . Patients with hypertension and diabetes benefit from the use of these drugs, since not only ACE2 is insensitive to blockade by ACE1 inhibitors, but also, the use of these inhibitor drugs increases the ACE2 gene expression and activity, probably due to an accumulation of Ang I [26] . ACE2 has been found to have protective effects against lung injury in different lung injury animal models [8, 27, 28] . Specifically, in diabetes, ACE2 seems to have a protective role in the progression of cardiovascular and renal complications and has been suggested as a potential therapeutic target for the management of diabetes and its complications [29, 30] . Studies in mice showed the role of ACE2 in the improvement of glycemia levels in mice with diabetes by direct effects in the pancreas [19] , improving insulin sensitivity and glucose-mediated insulin release [31] and reduction of the risk of type 2 diabetes development [32] . The effect of diabetes in the expression of ACE2 is not well established. Studies in animal models of diabetes evidenced either an increased or reduced expression of ACE2 in renal tissues and pancreatic tissues, depending on the disease stage. On contrary, the levels of ACE2 in lung tissue of mice with diabetes seem to be lower when compared to renal and pancreatic tissues [29, 33] . Similarly, a study in non-obese diabetic (NOD) mouse model showed an increase of ACE2 in serum, liver and pancreas, but not in the lung [34] . A study performed in 2012 by Soro-Paavonen et al. showed increased serum ACE2 activity in type 1 Diabetes mellitus (DM) patients with vascular complications but not in those without complications [35] . It has been found that ACEIs and angiotensin II receptor blockers (ARBs) cause an overexpression of ACE2 in patients treated with these drugs [26] . In the study of Soro-Paavonen, patients treated with ACEIs had increased ACE2 activity, independently of the presence of vascular complications [35] . However, the expression of ACE2 mRNA was not measured. Expression levels of ACE2 have been associated with susceptibility to SARS-CoV and SARS-CoV-2 infection in different cell lines [7, 36, 37] , therefore, raising the concern that patients being treated with ACEIs or ARBs could be at higher risk of infection and of associated morbidity and mortality after a SARS-CoV-2 infection, due to a higher expression of the virus' entry gate in target tissues [38] . Nevertheless, conflicting information has been found on this topic and some data suggest that ACEIs and ARBs can have protective effects against lung injury [39] . With relatively few clinical studies on this matter, when compared to the preclinical studies in animal models, it may be erroneous to admit that the effects of RAS inhibitors on ACE2 expression are translatable to human physiology. Additionally the measurements of ACE2 plasma levels, performed in most studies, may not be a reliable indicator of ACE2 activity, since the full length protein is predominantly membrane bound [39] . Taking advantage of ACE2, SARS-CoV-2 gains access to the cells, however it has been shown that soon after infection ACE2 expression is rapidly downregulated [8] . Whether this effect is caused by the virus, to prevent ACE2 protective effects [28] , or results from an indirect mechanism is not yet clear. It has been confirmed in some clinical studies that the long-term use of ACEIs or ARBs by patients is not associated with an increased risk of SARS-CoV-2 infection, neither of developing severe COVID-19 or even with a higher risk of in-hospital death [40] [41] [42] . All these studies highlight that the withdrawal of these medications is not recommended to prevent serious COVID-19, since these have well-known benefits in protecting the kidney and myocardium, [39] with the clinical decompensation caused by its removal potentially causing a more serious condition than the viral infection. The multi-organ damage is characteristic of SARS, nevertheless the major affected organs include the lungs, heart and kidney. The severity of disease progression and death predictor factors include old age, thrombocytopenia, severe hypoxia and hyperglycemia [43] . Hyperglycemia can also be a consequence of the SARS-CoV infection, due to the ACE2dependent damage of pancreatic islets and exocrine tissue, as islet damage, elevation on fasting plasma glucose levels and diabetes development during hospitalization have all been reported [43] . Although the pancreas damage was transient to most patients, in some cases diabetes remained after 3-years follow-up [43] . In the case of SARS-CoV-2 the same transient damage in the pancreas has already been documented [44] , and given its higher infectivity and affinity for the ACE2 receptor, there is increased concern relative to the complications caused by hyperglycemia, as well as the long-term effects of the infection on recovered patients. Hyperglycemia is characteristic of diabetes, when this chronic metabolic disorder is left untreated, which leads to serious complications ranging from limb amputations, kidney failure, blindness or cardiovascular disease [45, 46] . This disorder may be caused by insufficient insulin production by the pancreas, resistance to insulin action or a mixture of both [46] . Therefore, as hyperglycemia underlies many of the complications developed in the disease course, a tight control of glucose blood levels in patients with diabetes is essential. Since the beginning of COVID-19 outbreak, diabetes has been reported as one of the high-risk factors for rapid disease progression and bad prognosis of COVID-19 [47] . For instance, a retrospective cohort study with 191 Chinese patients infected with SARS-CoV-2 showed that 48% of the patients had a comorbidity, with diabetes representing 19% of those patients [48] . Another study showed that among 26 deaths due to SARS-CoV-2 in Wuhan, 42.3% had diabetes [49] . Also, a different cohort study analyzing 201 patients from Wuhan with confirmed COVID-19 pneumonia revealed that 10.9% of the patients had diabetes. They also observed that among the patients who developed acute respiratory distress syndrome (ARDS) (41.8% from the total cohort), more patients had comorbidities than those who did not develop ARDS, being diabetes the second most frequent comorbidity (19.0% in ARDS-patients versus 5.1% in non-ARDS patients) [50] . Furthermore, the largest case series of COVID-19 in China, reported by the Chinese Center for Disease Control and Prevention, showed that DM patients had higher mortality rates (7.3%) when compared to overall population (2.3%) in a total of 72,314 analyzed cases [51] . This comes as no surprise, as it is reported that people with diabetes demonstrate higher susceptibility to several infectious diseases, such as tuberculosis, pneumonia or influenza [52] . The underlying mechanisms are not completely understood and depend on the type of infection, but some hypotheses have been raised. Some possible explanations for DM being a high-risk factor for COVID-19 may be due to hyperglycemic environment, which is known to increase the virulence of some pathogens. Besides, it was also reported that phagocytosis and chemotaxis are impaired, the production of interleukins in response to infection is reduced, as well as the response of T cells and neutrophils [52, 53] . Overall, the immune response, which is vital to fight against COVID-19 infection, is impaired, especially in diabetic patients with poor blood glucose control. Furthermore, several studies have shown that DM patients have a significant decrease in forced vital capacity (FVC) and forced expiratory volume in one second (FEV1), which are important indicators of lung function. This impaired pulmonary function was significantly associated with poorly controlled diabetes and consequently hyperglycemic levels [54] [55] [56] . Therefore, this reduced pulmonary capacity may also increase susceptibility to respiratory infections, possibly representing another factor in the myriad of events that might increase the vulnerability of DM patients towards COVID-19. In the absence of a specific antiviral drug, physicians are considering and trying lopinavir, ritonavir, interferon-1b, RNA polymerase inhibitor, remdesivir and tamiflu that were already reported for other diseases [57] . Inclusively, zinc oxide nanoparticles have also been considered, since they were shown to have inhibitory effects on H1N1 viral load [58] . Plus, vitamin C is also a good supplement for the immune system and has some preventive effects on pneumonia [59] . However, none of these have shown yet evidences of being beneficial for COVID-19. As mentioned, it is suggested that therapeutics for diabetes and hypertension, namely ACEIs and ARBs, are responsible for upregulating ACE2. On the other hand, this is the functional receptor that SARS-CoV-2 uses as cellular entry [9] . In this sense, some authors hypothesize that these therapeutics may contribute for the increased infection and advice to discontinue ACEIs and ARBs, used in patients with diabetes or hypertension. However, there is no clear evidence in animals nor humans confirming this theory. Besides, ACE2 can also be increased by thiazolidinediones and ibuprofen, as well as exercise and dehydration. Plus, it was very recently published a Chinese study showing that transplantation of ACE2-mesenchymal stem cells improves the outcome of patients with COVID-19 pneumonia [60] . Some studies have actually already shown that overexpressed ACE2 plays a protective role in the lungs with SARS-CoV-2 infection, suggesting ARBs and ACEIs as therapy [61, 62] . As proof, in a preclinical study, authors injected animals with the spike glycoprotein of SARS-CoV, to cause a severe lung injury and verified that ACE2 is significantly downregulated. After treating them with ARB losartan, the severe acute lung injury was attenuated [8] . This evidence was supported by findings from China, where they showed that ACE2 blockade resulted in exacerbated lung damage and reduced animal survival after respiratory syncytial virus infection [28] . Actually, there is a comment from an Israel author, published in early March, proposing ARBs and ACEIs as a treatment for patients with COVID-19 infection to reduce the risk or severity of viral pneumonia [63] . However, when the coronavirus spike protein binds to ACE2, there is a downregulation of ACE2, which leads to an excessive accumulation of angiotensin II (vasoconstrictor, pulmonary inflammation, fibrosis, edema) and less ACE2 to convert it to angiotensin 1-7 (vasodilator, anti-proliferative, cytoprotective). The big question here is to know who wins this battle: the virus that binds to ACE2, which is upregulated in lungs, or the protective effects caused by the ACE2 upregulation. And this is not clarified yet. In this sense, European Medicines Agency (EMA) recommend that treatment with ARBs and ACEIs should be maintained in patients with diabetes and hypertension [64] . Patients who stop taking them may face more complications regarding kidney failure and increased mortality. Either way, as an alternative treatment, calcium channel blockers (CCBs) can be used, since they seem not to increase ACE2 expression and activity [65] . Commonly, and according to standard procedure, very sick patients should stop taking metformin and sodium-glucose transporter 2 inhibitors, due to their adverse side effects, as acidosis and fat metabolism [66] . In addition, the glucagon-like peptide receptor-1 analogues can also be stopped, since they may cause nausea, vomiting, and pioglitazone, among other side effects described elsewhere [67] . Plus, aromatase inhibitors should also be stopped since they reduce insulin sensitivity and insulin should be the only one used in acutely sick patients or with severe breathing disorders [68] . Only when recovered or stabilized, noninsulin therapy can be introduced. Knowing that the virus infection is a multistep process, there are some possible targets to treat COVID-19. A strong candidate that could exert a potent antiviral effect is the anti-malaria chloroquine. It is described that the virus processing and internalization is facilitated by low pH and pH-dependent endosomal cysteine protease cathepsins [69] . Chloroquine becomes entrapped in membrane-enclosed low pH organelles and is rapidly protonated and concentrated in endosomes, interfering with their acidification. Hydroxychloroquine has been then considered for short-term treatment trials [70] . The antiviral activity of chloroquine combined with azithromycin against COVID-19 in vitro was recently reported. However, the authors found no evidence of a strong antiviral activity or clinical benefit of this combination for the treatment of hospitalized patients with severe COVID-19. Either way, ongoing randomized clinical trials with hydroxychloroquine should provide a definitive answer regarding the alleged efficacy of this combination and will assess its safety [71] . Also, amiodarone has the ability to interfere with the endocytic pathway, being suggested as a possible inhibitor of the SARS coronavirus [72] . After binding to ACE2, the virus requires the essential serine protease, TMPRSS2, for S protein priming. So, using TMPRSS2 inhibitors (e.g. camostat mesylate), already used to treat cancer and hepatitis, can be a possible or adjuvant therapy [73] . According to EMA, the potential treatments that are in clinical trials are: remdesivir (investigational), lopinavir/ritonavir (anti-HIV), chloroquine and hydroxychloroquine (antimalaria and rheumatoid arthritis), systemic interferons as interferon beta (multiple sclerosis) and monoclonal antibodies with activity against components of the immune system [74] . Plus, all the diagnostics, treatments and vaccines considered for COVID-19 are summed up in Artis Ventures platform [75] . Overall, the chance of developing serious complications due to SARS-CoV-2 infection is higher in people with more health conditions associated. As discussed above, diabetes and all the complications associated with this disease, such as weakened immune response or hyperglycemia, present a higher risk for infected patients (Figure 1) . Not only for the COVID-19 progression, but also as a higher risk to develop secondary infections and therefore worsening of the health state. For those reasons, an effective and tight management of diabetes, specifically of glucose plasma levels, is extremely important in infected patients with diabetes. Additionally, while the use of ACEIs and ARBs in SARS-CoV-2 infected patients has raised some questions regarding their beneficial or harmful effects on disease progression, there is not enough evidence yet that allows drawing conclusions on this issue. Therefore, while care must be taken in the use of these drugs, their abrupt withdrawal is not recommended as it could lead to even more serious complications. Several strategies are being tested to control the COVID-19 pandemic and a better understanding of the SARS-CoV-2 effects on high-risk patients is fundamental to decrease the morbidities and mortality. European Centre for Disease Prevention and Control. Situation Update Worldwide, as of 23 Genomic Characterisation and Epidemiology of 2019 Novel Coronavirus: Implications for Virus Origins and Receptor Binding. The Lancet Genomic Characterization of the 2019 Novel Human-Pathogenic Coronavirus Isolated from a Patient with Atypical Pneumonia after Visiting Wuhan. 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Diabetes Angiotensin-Converting Enzyme Inhibitors, Angiotensin Ii Receptor Blockers and Diabetes: A Meta-Analysis of Placebo-Controlled Clinical Trials Angiotensin-Converting Enzyme Inhibitors or Angiotensin Receptor Blockers for Prevention of Type 2 Diabetes: A Meta-Analysis of Randomized Clinical Trials Glomerular Localization and Expression of Angiotensin-Converting Enzyme 2 and Angiotensin-Converting Enzyme: Implications for Albuminuria in Diabetes Characterization of Ace and Ace2 Expression within Different Organs of the Nod Mouse Circulating Ace2 Activity Is Increased in Patients with Type 1 Diabetes and Vascular Complications Susceptibility to Sars Coronavirus S Protein-Driven Infection Correlates with Expression of Angiotensin Converting Enzyme 2 and Infection Can Be Blocked by Soluble Receptor. Biochemical and Biophysical Research Communications Ace2 Receptor Expression and Severe Acute Respiratory Syndrome Coronavirus Infection Depend on Differentiation of Human Airway Epithelia Are Patients with Hypertension and Diabetes Mellitus at Increased Risk for Covid-19 Infection? 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The Lancet Characteristics of and Public Health Responses to the Coronavirus Disease Risk Factors Associated with Acute Respiratory Distress Syndrome and Death in Patients with Coronavirus Disease Characteristics of and Important Lessons from the Coronavirus Disease 2019 (Covid-19) Outbreak in China: Summary of a Report of 72 314 Cases from the Chinese Center for Disease Control and Prevention Infections in Patients with Diabetes Mellitus: A Review of Pathogenesis Common Infections in Diabetes: Pathogenesis, Management and Relationship to Glycaemic Control Lung Function and Glucose Metabolism: An Analysis of Data from the Third National Health and Nutrition Examination Survey Cross-Sectional and Prospective Study of Lung Function in Adults with Type 2 Diabetes: The Atherosclerosis Risk in Communities (Aric) Study. 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Ema Advises Continued Use of Medicines for Hypertension, Heart or Kidney Disease During Covid-19 Pandemic Calcium-Channel Blockers for Treatment of Diabetic Nephropathy An Update on Sodium-Glucose Co-Transporter-2 Inhibitors for the Treatment of Diabetes Mellitus. Current Opinion in Endocrinology Adverse Effects of Glp-1 The Review of Diabetic Studies Aromatase Inhibition Reduces Insulin Sensitivity in Healthy Men Should Covid-19 Concern Nephrologists? Why and to What Extent? The Emerging Impasse of Angiotensin Blockade Chloroquine Is a Potent Inhibitor of Sars Coronavirus Infection and Spread No Evidence of Rapid Antiviral Clearance or Clinical Benefit with the Combination of Hydroxychloroquine and Azithromycin in Patients with Severe Covid-19 Infection Amiodarone Alters Late Endosomes and Inhibits Sars Coronavirus Infection at a Post-Endosomal Level Sars-Cov-2 Cell Entry Depends on Ace2 and Tmprss2 and Is Blocked by a Clinically Proven Protease Inhibitor Update on Treatments and Vaccines against Covid-19 under Development Fight the Pandemic This work was financed by FEDER -Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 -Operacional Programme for Competitiveness and 


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   key: cord-269856-6h3j89wn authors: Paolo Fadini, Gian; Luca Morieri, Mario; Boscari, Federico; Fioretto, Paola; Maran, Alberto; Busetto, Luca; Maria Bonora, Benedetta; Selmin, Elisa; Arcidiacono, Gaetano; Pinelli, Silvia; Farnia, Filippo; Falaguasta, Daniele; Russo, Lucia; Voltan, Giacomo; Mazzocut, Sara; Costantini, Giorgia; Ghirardini, Francesca; Tresso, Silvia; Maria Cattelan, Anna; Vianello, Andrea; Avogaro, Angelo; Vettor, Roberto title: Newly-diagnosed diabetes and admission hyperglycemia predict COVID-19 severity by aggravating respiratory deterioration date: 2020-08-15 journal: Diabetes Research and Clinical Practice DOI: 10.1016/j.diabres.2020.108374 sha: doc_id: 269856 cord_uid: 6h3j89wn Abstract Aims We investigated whether pre-existing diabetes, newly-diagnosed diabetes, and admission hyperglycemia were associated with COVID-19 severity independently from confounders. Methods We retrospectively analyzed data on patients with COVID-19 hospitalized between February and April 2020 in an outbreak hospital in North-East Italy. Pre-existing diabetes was defined by self-reported history, electronic medical records, or ongoing medications. Newly-diagnosed diabetes was defined by HbA1c and fasting glucose. The primary outcome was a composite of ICU admission or death. Results 413 subjects were included, 107 of whom (25.6%) had diabetes, including 21 newly-diagnosed. Patients with diabetes were older and had greater comorbidity burden. The primary outcome occurred in 37.4% of patients with diabetes compared to 20.3% in those without (RR 1.85; 95%C.I. 1.33-2.57; p<0.001). The association was stronger for newly-diagnosed compared to pre-existing diabetes (RR 3.06 vs 1.55; p=0.004). Higher glucose level at admission was associated with COVID-19 severity, with a stronger association among patients without as compared to those with pre-existing diabetes (interaction p<0.001). Admission glucose was correlated with most clinical severity indexes and its association with adverse outcome was mostly mediated by a worse respiratory function. Conclusion Newly-diagnosed diabetes and admission hyperglycemia are powerful predictors of COVID-19 severity due to rapid respiratory deterioration. Diabetes worsens the outcome of virtually any acute or chronic medical condition, resulting in a shortened life expectancy [1] . Mortality from infectious disease is also increased in patients with diabetes, especially for sepsis and pneumonia [2] . Since the very beginning of the SARS-CoV-2 pandemic, diabetes emerged as one of the most common comorbidities and a potential driver of poor outcomes [3] . The prevalence of diabetes was higher among patients hospitalized for COVID-19 who were admitted to the intensive care unit (ICU) or died [4] . Meta-analyses of studies reporting the characteristics of patients according to COVID-19 severity in China found that diabetes conferred a 2-3 fold increased rate of poor disease outcome [5, 6] . These findings are in line with the available literature on the adverse prognostic impact of diabetes on other viral infections, including influenza [7, 8] . It remains unclear whether diabetes drove such excess risk independently from confounders, including its complications and comorbidities. It is conceivable that patients with diabetes experienced a worse COVID-19 outcome because of multiple organ damage due to micro-and macrovascular disease [9, 10] . On the other side, whether the impact of diabetes on COVID-19 outcome depends on glucose control is less appreciated. In a study conducted on 7337 Chinese patients, diabetes was associated with higher mortality, but patients with good glycemic control had lower mortality compared to those with poorer control [11] . Optimal glycemic management can therefore be crucial to improve COVID-19 outcome [12] . Finally, new-onset diabetes has been reported during COVID-19 [13] [14] [15] , but its impact on disease outcome has not been assessed. In patients with acute medical conditions, such as acute myocardial infarction, newly-detected diabetes has an adverse prognostic effect [16, 17] . Of note, newly-diagnosed diabetes is often linked with occult organ damage that shortens survival [18] . In addition, stress hyperglycemia has been known for decades to drive an exaggerated inflammatory response in critically-ill individuals [19] . In the present study, we investigated the role of pre-existing diabetes, newly-diagnosed diabetes, and admission glucose levels on the outcome of patients hospitalized for COVID-19. We eventually explored which were the mediators of a poor outcome associated with diabetes. This retrospective study was conducted by collecting anonymized patient's data from electronic medical records. The protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. In agreement with national regulation on retrospective studies, the protocol was notified to the local ethical committee (no. 0031264) and the need for patient's informed consent was waived. We retrieved data on all consecutive patients hospitalized for COVID-19 between February 21 st and April 20 th 2020 at the University Hospital of Padova, which is located at the center of one of the first SARS-CoV-2 outbreaks in Northern Italy. We screened records of all patients admitted to the Hospital with a positive PCR test for SARS-CoV-2 on upper or lower airway sample. Pre-existing diabetes was defined based on self-reported history, prior electronic medical records reporting a diagnosis of diabetes, or ongoing therapy with glucose-lowering medications. Newly-diagnosed diabetes was defined by a HbA1c value of 48 mmol/mol (6.5%) or higher; in the absence of an HbA1c determination, a random glucose level of 11.1 mmol/l (200 mg/dl) or higher, accompanied by signs and symptoms of hyperglycemia was considered diagnostic. For all patients, we recorded the following information: demographics (age, sex), concomitant cardiovascular risk factors (smoke, hypertension, dyslipidemia), comorbidities (chronic obstructive pulmonary disease and history of cancer), complications (cardiovascular disease and microangiopathy), presence or absence of COVID-19 related pneumonia or interstitial lung disease (ILD), ongoing therapies before hospitalization. We collected information on symptoms of COVID-19 upon admission (time from onset of symptoms to hospitalization; presence of fever, cough, dyspnea, and gastrointestinal symptoms). Vital signs were recorded at admission and at their worst timepoint: systolic and diastolic blood pressure, heart and respiratory rate, oxygen saturation, PaO 2 / FiO 2 ratio. Key laboratory exams included: fasting plasma glucose, HbA1c, lipid profile (total cholesterol, HDL cholesterol, triglycerides, and calculated LDL cholesterol), and serum creatinine for calculation of estimated glomerular filtration rate (eGFR) using the CKD-EPI equation. We also collected admission levels and worse levels of the following biomarkers related to inflammation (white blood cell count [WBC], C-reactive protein [CRP], IL-6, pro-calcitonin), hematology and coagulation (hemoglobin, lymphocytes, platelets, D-dimer) and tissue injury (liver enzymes, troponin I, lactate). We reported the worst vital signs or biomarkers as the worst value measured during the entire hospital stay, regardless of whether it occurred at admission or during any other time of hospitalization. In some cases, worst values could coincide with admission values if admission values were the worst among all values recorded during the hospital stay. The following in-hospital treatments were recorded: low-flow and high-flow oxygen, non-invasive ventilation, intubation, use of specific drugs, such as lopinavir/ritonavir, azithromycin, other antibiotics, remdesivir, chloroquine / hydroxychloroquine, glucocorticoids, tocilizumab. The primary outcome was a composite of admission to the ICU (including all subjects needing mechanical ventilation) or death. Death from any cause, was considered as a separate outcome. Among those who were discharged alive, time to discharge was considered as additional secondary outcomes. Because duration of hospitalization was highly skewed and sometimes driven by non-clinical reasons (e.g. patients being unable to return to home because lacking social support), observation was censored at 30 days. Continuous variables are reported as mean ± standard deviation (SD) or as median (inter-quartile range), while categorical variables have been reported has percentages. Between-group differences in clinical characteristics were evaluated with Student t-test or chi-Square for continuous and categorical variables, respectively. The association between diabetes, glucose levels and other variables of interest with categorical outcomes was evaluated with robust-error-variance Poisson regression models [20] . In order to identify possible confounding factors, these associations were tested in unadjusted models and in two different multivariable adjusted (MVA) models with increasing complexity. Model 1 (MVA1): adjusted for sex and age. Model 2 (MVA2): adjusted for sex, age and pre-existing conditions or pre-hospital medications associated with COVID-19 severity in MVA1. In order to test the MVA, full dataset of variables were needed, thus missing data were handled by means of multiple imputation (MI). MI was performed with a fully conditional specification (FCS) algorithm [21] obtaining 10 imputed datasets including only covariates with less than 60% of missing values. Outcome variables and main variables of interest (e.g. plasma glucose) were not imputed. Outcome analyses were performed on each imputed dataset and the pooled estimated effects are presented [22] . Cox proportional hazard model was used to compare the patient's probability of being discharged alive. The differences between the association of pre-existing diabetes and newly-diagnosed diabetes with the primary and secondary outcomes were evaluated by means of Z score (Z score = (estimates 1 -esitmates 2 ) / √(SE 1 2 +SE 2 2 )). The differences in the association between glucose levels and primary outcome among subjects with or without diabetes was evaluated with the inclusion of an interaction term in the models. The association between fasting plasma glucose and the worst levels of clinical and laboratory parameters detected during hospital stay were represented graphically with scatter plots and described by Pearson' r correlation coefficient. We evaluated which of these parameters explained the association between glucose levels and COVID-19 severity outcome (i.e. being mediators). To be consider a candidate mediator, variables needed to be independently associated with both the primary outcome (tested using Poisson regression with robust error variance) and with glucose levels (tested with linear regression). For those variables meeting these two conditions, we then quantified the possible mediation effect (in percentage) as the differences in the association between glucose and the primary outcome in the model adjusted by the candidate mediator (RR ADJUST ) as compared to the association in the model not adjusted by the candidate mediator (RR NOT-ADJUST ). Therefore the mediation analyses was evaluated as: mediation = 100 x [ln(RR NOT-ADJUST )-ln(RR ADJUST )]/ln(RR NOT-ADJUST ). Statistical analyses were conducted with a significance threshold of p<0.05 and were done in SAS version 9.4 (TS1M4), GraphPad PRISM v8.3.0. We included 413 patients who tested positive for SARS-CoV-2 upon PCR analysis. Of these, 107 (25.6%) had diabetes (86 pre-existing and 21 newly diagnosed). As compared to individuals without diabetes, those with diabetes were older, had a higher prevalence of hypertension, dyslipidemia, cardiovascular disease, and chronic kidney disease. In addition, preadmission use of statins, antiplatelet drugs and beta-blockers were more common among subjects with diabetes (Table 1 ). Symptoms at admission were similar as were laboratory findings (except for FPG and HbA1c). Participants with diabetes had more compromised respiratory function with lower PaO 2 /FiO 2 and higher respiratory rate (Table 2 ). In-hospital pharmacological treatments were similar in subjects with or without diabetes, except that diabetic patients more often received antibiotics other than macrolids (Table 2) . Table S1 shows patients' clinical characteristics further stratified by pre-existing versus newly-diagnosed diabetes status. Over a median observation time of 17 days (IQR 6-26), 102 patients (24.7%) showed a severe course, defined as the primary outcome, 48 of whom died (11.6%). In unadjusted analysis, presence of diabetes (including pre-existing and newly-diagnosed) compared to its absence was associated with a higher incidence of the primary outcome (37.4% vs 20.3%; RR 1.85; 95% C.I. 1.33-2.57; p<0.001; Figure 1A ). Several other pre-existing conditions were associated with COVID-19 severity, including hypertension, cardiovascular disease, atrial fibrillation, CKD and COPD (Table S2 ). Among prehospitalization treatments, use of ARBs, novel oral anticoagulants, and systemic glucocorticoids was more frequent among patients with the primary severity outcome (Table S2 ). Compared to absence of diabetes, newly diagnosed diabetes (RR 3.06; 95% C.I. 2.04-4.57) showed a stronger association with the primary outcome than pre-existing diabetes (RR 1.55, 95% C.I. 1.06-2.27). The difference in the RR for the primary outcome between pre-existing and newly-diagnosed diabetes was statistically significant (p=0.004). In addition, higher FPG at admission was associated with COVID-19 severity, with an increase in relative risk of 21% (RR 1.21; 95% C.I. 1.11-1.32; p<0.001) for each 2 mmol/L (36 mg/dl) increase in FPG. This association was stronger among individuals without diabetes than in those with diabetes (p for interaction = 0.003; Figure 1A) After adjusting for age and sex, the magnitude of the association between diabetes (pre-existing and newlydiagnosed altogether) and COVID-19 severity remained significant (RR 1.49; 95% C.I. 1.07-2.09; p=0.019; Figure 1B ). Other variables associated with severity in the age-and sex-adjusted analysis were chronic kidney disease and pre-hospitalization use of systemic glucocorticoids (Table S2 ). The analysis was repeated splitting diabetes into pre-existing and newly-diagnosed. The association of preexisting diabetes was attenuated and no longer significant, whereas the association between newly-diagnosed diabetes with the primary outcome remained statistically significant. The association between FPG and the primary outcome remained significant after age-and sex-adjustment and yet with a larger effect on outcome among non-diabetic than diabetic subjects ( Figure 1B ). We tested whether the associations of diabetes and FPG with COVID-19 severity was independent from additional confounders. As shown in Table S3 , the association between diabetes and the primary outcome was confirmed in all models, including those with preexisting comorbidities and medications used prior to hospitalization (RR 1.61; 95% C.I. 1.12-2.30; p=0.010). Similarly, the association between FPG and the primary outcome was confirmed in all models (Table S3) , including those with pre-existing comorbidities and medications used prior to hospitalization (RR per each 2 mmol/l = 1.14; 95% C.I. 1.06-1.23; p<0.001). We found a similar mortality rate among those with or without diabetes (10.8 vs 14.0%; unadjusted RR 1.30; 95% CI 0.74-2.30; p=0.367). Conversely, a significant association was detected between FPG and mortality (RR for each 2 mmol/L increase 1.15; 95% CI 1.03-1.30; p=0.017), but this association disappeared after adjustment for age and sex (RR 1.03; p=0.668). We also found that a lower proportion of diabetic patients was discharged alive during the observation time (56.1 % vs 77.8%; p<0.001; Table 2 ) with a longer mean time to discharge (+2.3 days; p=0.021; Table 2 ). In a time-to-event analysis, diabetes was associated with a 43% reduced probability of recovery after adjustment for age and sex (HR 0.58; 95% C.I. 0.43-0.77). Among survivors, the duration of hospitalization was significantly longer for patients with as compared to those without diabetes in unadjusted (+3.7 days; 95% C.I. 1.9-5.5, p<0.001; Table 2 ) and age-and sex-adjusted models (+2.6 days; 95% C.I. 0.9-4.6, p=0.003). For each 2 mmol/l higher FPG, there was a significant 19% lower probability of recovery (HR 0.82 95% C.I. 0.74-0.91; p <0.001) and longer duration of hospitalization (+1.0 days; 95% C.I. 0.5-1.5; p<0.001). We found statistically significant correlations between admission glucose levels and most clinical-laboratory characteristics, recorded at their worst level, indicative of COVID-19 severity or progression, including hemodynamic, respiratory, hematologic, inflammatory, and tissue damage biomarkers (Figure 2 ). We then evaluated whether these correlations could partially explain (i.e. mediate) the association between FPG and COVID-19 severity outcome. We first identified clinical-laboratory characteristics (recorded at their worst level) significantly associated with COVID-19 severity (independently from age and sex). Then, we estimated what percentage of the effect of FPG on COVID-19 severity was explained by the association between FPG and these variables. As described in Table S4 and represented graphically in Figure 3 , we found that a decline in respiratory function variables was the major determinant of the detrimental effect of hyperglycemia on COVID-19 severity. In this study, we found that newly-detected diabetes and admission hyperglycemia were more strongly associated with COVID-19 severity outcome than pre-existing diabetes. A known diabetes status was more common among patients with severe COVID-19, defined by ICU admittance or death. Known diabetes remained associated with poor COVID-19 outcome independently from age and sex, but not when adjusted for other baseline clinical variables, suggesting that such effect was mostly driven by concomitant factors and complications. On the other side, newly-detected diabetes remained associated with COVID-19 severity in fully-adjusted analyses. Upon a formal comparison, the association with the primary outcome was stronger for newly-diagnosed than for pre-existing diabetes. Admission glucose levels were closely related to most clinical and biochemical parameters of COVID-19 severity collected during hospitalization, including the PaO 2 /FiO 2 ratio. Remarkably, for each 2 mmol/l (36 mg/dl) higher admission glucose, the probability of severe progression significantly increased by about 15% independently from any other clinical-biochemical variable. The association between hyperglycemia and COVID-19 severity was significantly stronger for patients with newly-diagnosed diabetes than for those with pre-existing diabetes. Our finding is consistent with prior literature indicating that, in patients with acute medical conditions, newlydetected diabetes is a powerful predictor of poor outcomes [16, 23] . This may be at least in part driven by the fact that known diabetes is often associated with manifest organ damage that can be accounted for clinically and statistically [18] . Vice-versa, patients who are unaware of their diabetes status are most of the times unaware of ongoing organ damage too, as their treating physicians are. In addition, such occult organ damage cannot be accounted for in statistical adjustment. Yet, our data argue that newly-diagnosed diabetes was predictive of COVID-19 severity not only because of a possible masked multi-organ frailty, but also by the strong link between glucose levels and the outcome. We performed an analysis to evaluate which of the clinical-laboratory parameters of disease severity were mostly responsible for mediating the effect of hyperglycemia on the outcome. Top results included respiratory parameters and white blood cell count, whereas other markers of inflammation and tissue damage were not among top mediators, suggesting that hyperglycemia drove a worse progression of respiratory failure. Indeed, PaO 2 /FiO 2 directly reflects respiratory failure and drives ICU admittance or mechanical ventilation [24] . Diabetes and hyperglycemia were previously found to cause a form of pulmonary disease known as "diabetic lung", featuring changes in lung volumes and diffusion capacity [25] . Speculatively, patients with admission hyperglycemia upon hospitalization for COVID-19 might have a poorer outcome because of an underlying subclinical pulmonary remodeling [26] . The diabetic lung is supposed to be driven at least in part by obesity and metabolic syndrome [27] , but systemic inflammation and platelet dysfunction have been implicated in hyperglycemic pulmonary microangiopathy [28] . Since inflammatory overactivation and coagulopathy are major features of severe COVID-19 [29] , we speculate that hyperglycemia can directly accelerate disease course. The study has limitations that do not allow us to exclude alternative explanations. First, some clinical variables were not collected for all patients, due to the setting where COVID-19 patients were followed, i.e. strictly isolated wards with limited contacts with health personnel. Absence of data on body mass index (BMI) prevented us from adequately considering the confounding role of obesity [30, 31] . In addition, HbA1c was not available for all patients, potentially biasing the detection of pre-existing hyperglycemia. Although we were able to control for the use of pre-admission use of glucocorticoids, in most cases it was impossible to judge the duration of hyperglycemia prior to hospitalization for COVID-19 in patients without known diabetes. Therefore, whether these patients had undiagnosed diabetes or stress hyperglycemia due to the cytokine storm remains unclear. Despite our attempts to control for major biases, we cannot rule out that residual confounding was driving a spurious non-causal association between hyperglycemia and severe COVID-19. For example, a more severe degree of inflammatory activation before hospitalization could drive both stress hyperglycemia and a subsequent severe disease course, even if hyperglycemia exerted no direct role on disease progression. In other terms, it is impossible to rule out that hyperglycemia is simply a biomarker of a more severe disease [23] . Nonetheless, our study has notable strengths, including the detailed clinical characterization of patients with inclusion of several biochemical inflammatory markers, and the rigorous statistical approach to bias. Furthermore, the mediation analysis allows speculating on the processes that drove poor outcome of COVID-19 patients presenting with admission hyperglycemia. Finally, we wish to underline that, while this manuscript was under preparation, a study conducted on 453 patients hospitalized for COVID-19 at the Union Hospital in Wuhan (China) found that newly diagnosed diabetes was associated with a higher risk of mortality than known diabetes [32] . Interestingly, patients without known diabetes but presenting with hyperglycemia had the worst outcome. The similarities with our study are striking, providing evidence that COVID-19 presents with the same clinical features in distant countries and different healthcare models. This also markedly reinforces the clinical message that hyperglycemia is a strong prognostic factor for adverse outcomes during COVID-19. Data availability. Original data are available from the corresponding author at a reasonable request. When distribution of the dependent variable was highly skewed, the Y scale was log transformed. Table S4 . Diabetes mellitus, fasting glucose, and risk of cause-specific death Mortality from infectious diseases in diabetes. Nutrition, metabolism, and cardiovascular diseases : NMCD Practical recommendations for the management of diabetes in patients with COVID-19 Clinical Characteristics of Coronavirus Disease 2019 in China. The New England journal of medicine Diabetic patients with COVID-19 infection are at higher risk of ICU admission and poor short-term outcome Prevalence and impact of diabetes among people infected with SARS-CoV-2 Characteristics and outcome of viral pneumonia caused by influenza and Middle East respiratory syndrome-coronavirus infections: A 4-year experience from a tertiary care center Clinical courses and outcomes of hospitalized adult patients with seasonal influenza in Korea The contribution of diabetic micro-angiopathy to adverse outcomes in COVID-19. Diabetes research and clinical practice Clinical Characteristics and Risk Factors for Mortality of COVID-19 Patients With Diabetes in Wuhan, China: A Two-Center Association of Blood Glucose Control and Outcomes in Patients with COVID-19 and Pre-existing Type 2 Diabetes. Cell metabolism Outcomes in Patients With Hyperglycemia Affected by Covid-19: Can We Do More on Glycemic Control? Diabetes care COVID-19 symptoms masking inaugural ketoacidosis of type 1 diabetes Diabetic ketoacidosis precipitated by Covid-19 in a patient with newly diagnosed diabetes mellitus. Diabetes research and clinical practice COVID-19 infection may cause ketosis and ketoacidosis Diabetes known or newly detected, but not impaired glucose regulation, has a negative influence on 1-year outcome in patients with coronary artery disease: a report from the Euro Heart Survey on diabetes and the heart Cardiovascular outcomes using doxazosin vs. chlorthalidone for the treatment of hypertension in older adults with and without glucose disorders: a report from the ALLHAT study Prognostic significance of silent myocardial infarction in newly diagnosed type 2 diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS) 79 Stress-hyperglycemia, insulin and immunomodulation in sepsis A modified poisson regression approach to prospective studies with binary data Multiple Imputation by Fully Conditional Specification for Dealing with Missing Data in a Large Epidemiologic Study Multiple Imputation after 18+ Years Hyperglycemia: an independent marker of in-hospital mortality in patients with undiagnosed diabetes Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region Diabetic lung, an underrated complication from restrictive functional pattern to pulmonary hypertension The diabetic lung: an easy target for SARS-CoV-2? The metabolic syndrome, diabetes and lung dysfunction Diabetic Microvascular Disease and Pulmonary Fibrosis: The Contribution of Platelets and Systemic Inflammation COVID-19 cytokine storm: the interplay between inflammation and coagulation. The Lancet Respiratory medicine Predicting mortality due to SARS-CoV-2: A mechanistic score relating obesity and diabetes to COVID-19 outcomes in Mexico Obesity is associated with worse outcomes in COVID-19: Analysis of Early Data From Newly diagnosed diabetes is associated with a higher risk of mortality than known diabetes in hospitalized patients with COVID-19 


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   key: cord-274548-yeucn13x authors: Altobelli, Emma; Angeletti, Paolo Matteo; Profeta, Valerio F.; Petrocelli, Reimondo title: Lifestyle Risk Factors for Type 2 Diabetes Mellitus and National Diabetes Care Systems in European Countries date: 2020-09-13 journal: Nutrients DOI: 10.3390/nu12092806 sha: doc_id: 274548 cord_uid: yeucn13x Background. Diabetes is increasing by 3.09% per year in males and 1.92% in females. Lifestyle risk factors are related to diabetes. The aim of this work is to highlight within EU-28 countries the distribution percentages of some lifestyle risk factors and some components of diabetes health care. Methods. A literature search was conducted to highlight the presence of diabetes registries, which are fundamental tools for disease surveillance and health planning; the presence of a national diabetes plan (NDP); the care setting; and methods used for reimbursement of drugs, devices, and coverage of any comorbidities associated with diabetes. A multiple correspondence analysis (MCA) was carried out to evaluate the possible associations between the variables considered. Results. The highest percentages of diabetes (>10%) are registered in Bulgaria, Malta, and Hungary. Concerning the prevalence of overweight, no European country shows overall percentages of less than 50%. Regarding obesity, 57% of countries show prevalence rates of 25%. The record for physical inactivity belongs to Malta, with 45% of individuals being inactive. The percentage of physical inactivity for females is higher than for males across Europe. In total, 57% of the countries have an insurance-based health system, while 12 countries have public national health systems. Further, 57% of countries have an NDP, while 42% of the EU countries have established a prevalence register for diabetes. Conclusions. Prevalence rates for type 2 DM in the range of 8–9% are noted in 50% of EU-28 countries. In total, 21 out of EU countries show a high prevalence rate for overweight, while 7% of EU-28 countries have an obesity prevalence rate of 25%. Diabetes treatment is entrusted to general practitioners in most countries. The results of this work highlight the differences between countries, but also between genders. Type 2 diabetes mellitus represents the paradigm of chronic diseases in which there is a close association between family and environmental factors. It is now a health problem with enormous global impact, with estimates of continuous growth [1] . An important universally recognized risk factor is high calorie intake with limited intake of fiber, which results in an increased accumulation of visceral fat, an increase in body mass index (BMI), and increase in abdominal circumference [2] . Table 1 and Figures 1 and 2 summarize the information related to the income and distribution percentages of the following risk factors: overweight, obesity, physical inactivity, and type 2 diabetes. Data came from Eurostat datasets [32] and we used the Map Creator 2 software to build the maps (Figures 1 and 2) . A literature search was conducted to highlight the presence of diabetes registries as fundamental tools for disease surveillance and health planning ( A literature search was conducted to highlight the presence of diabetes registries as fundamental tools for disease surveillance and health planning ( Table 2 ). The keywords used were registries OR incidence OR prevalence AND diabetes mellitus; insulin-dependent registries OR incidence OR population based AND diabetes mellitus, insulin-dependent; "Prevalence" OR "Registries" OR "Population Based" AND "Diabetes Mellitus, Type 2" AND "Epidemiology"; considering publications from the last 10 years, in English, over 19 years of age. The PRISMA [33] method was used to select bibliographic entries ( Figure 3 ). Only references to type 2 diabetes registries were selected. The data covered the type of health system, presence or absence of a national diabetes plan (NDP), presence of a population-based register, care setting, methods for reimbursement of drugs, devices and coverage of any comorbidities associated with diabetes, and the prevalence of and mortality from diabetes, gathered from the institutional sites of individual European countries to investigate the presence of national data and policies for diabetes control. Furthermore, to ensure the completeness of the data, the following sources of information were consulted: EUROSTAT [32] , WHO diabetes country profiles [34] , European Commission (EC) [35], International Federation of Diabetes (IFD) [1], Foundation of European Nurses for Diabetes (FEND) [36] , and the World Bank [37] . All data are reported in Table 3 . Full-text articles excluded, with reasons n = 48 type 1 diabetes registries n=14 paper without Studies included in qualitative synthesis (n = 18) (n = 9 EU-28 countries n = 9 outside EU-28 countries) The data covered the type of health system, presence or absence of a national diabetes plan (NDP), presence of a population-based register, care setting, methods for reimbursement of drugs, devices and coverage of any comorbidities associated with diabetes, and the prevalence of and mortality from diabetes, gathered from the institutional sites of individual European countries to investigate the presence of national data and policies for diabetes control. Furthermore, to ensure the completeness of the data, the following sources of information were consulted: EUROSTAT [32] , WHO diabetes country profiles [34] , European Commission (EC) [35], International Federation of Diabetes (IFD) [1], Foundation of European Nurses for Diabetes (FEND) [36] , and the World Bank [37] . All data are reported in Table 3 . A multiple correspondence analysis (MCA) was carried out in order to to evaluate the possible association between the variables taken into consideration, including EUROSTAT data for the countries of the European Union, data relating to mortality per 100,000 inhabitants and the mortality trend [32] , the prevalence of diabetes [32] , the organization of the health system [35, 36, 38] , the presence of a national diabetes plan, the year of approval [35, 36] , the general practitioners and diabetic centers involved, and the cost percentage of diabetes of the total health expenditure [38] . The variables listed above were classified as follows: percentage of diabetes (≤6%, >6%), diabetes mortality (≤25 per 100,000, greater than >25 per 100,000), mortality trend (growth, stable and in reduction), and percentage cost of diabetes of total health expenditure (≤9%, >9%). The MCA was conducted using SAS statistical software. The graphical representation takes into account the variables that contributed most to the variance. Countries belonging to the European Union show high income rates, except for Bulgaria and Romania. The highest percentages of diabetes (>10%) are registered in Bulgaria, Malta, and Hungary. Values for diabetes of between 8 and 9% are shown for 50% of the countries, including the Czech Republic, Croatia, Estonia, France, Italy, Greece, Lithuania, Latvia, Poland, Portugal, Romania, Slovakia, Slovenia, and Spain; while values between 6 and 7% are shown for Austria, Belgium, Cyprus, Denmark, Finland, Luxembourg, Germany, Ireland, Sweden, the United Kingdom, and the Netherlands. Regarding men, seven countries (25%) have a diabetes percentage rate higher than 10%: Bulgaria, Czech Republic, Estonia, Hungary, Malta, Spain. Regarding women, Bulgaria shows a rate of 10%. Concerning overweight individuals, no European country shows overall percentages of less than 50%. In fact, as many as 21 out of 28 countries (75% of European countries) show a high percentage of overweight of 60%; the remaining 7 countries show percentages of between 50 and 60%. Overweight affects 70% of men in 6 countries (Czech Republic, Estonia, Luxembourg, Malta, Spain, and UK) and percentages between 60-70% are shown for 21 states. Only Latvia has a percentage just below 60%. The figures for women are globally similar, with the exception of Austria, where the percentage of overweight is slightly lower (49.2%). In 17 out of 28 countries, the percentage of female overweight is between 50 and 60%, while in 10 countries the percentage exceeds 60% (Czech Republic, Denmark, Estonia, Greece, Latvia, Lithuania, Malta, Poland, Spain, UK). Regarding obesity, 57% of European countries show values of obesity of 25%: Bulgaria, Croatia, Czech Republic, Estonia, France, Greece, France, Hungary, Ireland, Latvia, Lithuania, Malta, Poland, Slovakia, Slovenia, Spain, UK). Percentages in the range of 23.4-24.5% are shown for Cyprus, Italy and Romania. The remaining countries show obesity percentages ranging between 20 and 22%. Regarding gender, obesity rates are above 28% for men in 4 countries (Czech Republic, Estonia, Luxemburg, UK), while the lowest values are recorded in Austria, Portugal, and Romania. Particularly relevant is that in some countries (Czech Republic, Malta, Estonia, and UK) the percentage of obese women is greater than 30%. Instead, the percentage exceeds 25% in 11 countries (Bulgaria, Cyprus, France, Hungary, Ireland, Lithuania, Poland, Slovakia, Slovenia, and Spain). On the other hand, the percentages of physical inactivity are more variable from country to country. The highest value for physical inactivity belongs to Malta with 45%, followed by countries in southern Europe (Italy, Spain, Portugal) and northern Europe (Belgium and the United Kingdom). It is important to underline that the percentage of physical inactivity in females is higher than in males across Europe. A total of 12,150 references were identified through database searching were, while 40 were identified through manual searching. Of these, 45 references were excluded because they were duplicates. Of the remaining papers, 80 were selected as potentially valid for the systematic review. Nutrients 2020, 12, 2806 9 of 14 A further 14 papers were excluded for not containing the requested information. In total, 66 papers were analyzed, of which 48 covered type 1 DM and 18 covered type 2 DM (Figure 3 PRISMA Flow Chart). Of the latter 18, 9 were EU-28 countries and 9 were from outside the EU-28. All results are described in Table 2 . European health systems vary from country to country, and even within individual countries. However, in most European countries (57%) there are insurance-based health systems, while in 12 countries there are public national health systems. In 57% of countries, there are national diabetes plans. In total, 42% of the countries belonging to the European Union have established a prevalence register for diabetes. Diabetes care is mainly entrusted to the general practitioner in 19 countries, while in the remaining countries it is entrusted to diabetes centers. In health systems where health care is totally managed by the state government, the latter provides coverage for drugs, devices, and associated comorbidities, except for Latvia. In insurance systems, on the other hand, only in Belgium is there full coverage for expenses relating to drugs, devices, and comorbidities, while in the remaining countries there are shares for different copayments. Mortality is extremely variable; the lowest values are found in Finland, while the highest values are present in the islands Malta and Cyprus. There are only two countries with values above 40/100,000, which are Croatia and Czech Republic; while mortality values of between 30 and 40/100.00 are found in Austria, Portugal. and Hungary. Seven out of 28 countries show mortality values of between 20 and 30, including Bulgaria, Denmark, Germany, Italy, Latvia, Poland, and Sweden. In total, 42% of European countries show mortality values of between 10 and 20/100,000, including Belgium, Estonia, France, Greece, Ireland, Lithuania, Luxembourg, Romania, Slovakia, Spain, UK, and the Netherlands. The country and year of approval of each national diabetes plan represent the first dimension, which account for about 35% of the variance; the prevalence and mortality trends represent the second dimensions, which account for around 25% of the variance. All results are represented in Figure 4 . Nutrients 2020, 12, x FOR PEER REVIEW 10 of 14 trend, and a health expenditure for diabetes <9% of the total national health expenditure. The cloud of points represents the presence of an NDP, health expenditure for diabetes <9%, and the presence of the national health service. The chronicity control system is represented by the chronic care model (CCM), which was developed in the mid-1990s by Wagner [39, 40] . This model covers the needs of health organizations and citizens. The CCM provides six levels of implementation: the organization of care systems with the removal of barriers; self-management with support from a caregiver; support for decisions on prevention or treatment strategies based on medical evidence; delivery of services; a system for recording and monitoring care and community and public health resources [41] . For diabetes mellitus, this means a combination of programs The first quadrant includes the following countries and variables-Finland, the United Kingdom, Ireland, Sweden, Belgium, Austria, Luxembourg, the Netherlands, each showing a mortality rate below 25.0, diabetes <6%, stable mortality trend, and with diabetes care entrusted to general practitioners. In this quadrant, a cloud of points can be seen, showing mortality <25/100,000 diabetes <6% for Austria and Netherlands, with diabetes care entrusted to general practitioners. The following countries and variables represent the second quadrant-Estonia, Bulgaria, Poland, Romania, Lithuania, Latvia, France, and Germany, each showing health expenditure for diabetes >9% compared to the total health expenditure, an increasing mortality trend, the absence of a national diabetes plan for diabetes, and health insurance. In this quadrant, an aggregation zone can be highlighted, which includes the absence of a national diabetes plan, a rising mortality trend, and health insurance. Hungary, the Czech Republic, Slovenia, Greece, Croatia, Cyprus, Malta, and the geographical area of Eastern Europe represent the third quadrant, each having a mortality rate greater than 25%, the approval after 2003 of the NDP, a % of diabetes >6%, and the presence of diabetes services. It is important to underline that a point of clouds includes mortality greater than 25%, percentage of diabetes >6%, and approval year of the NDP after 2003. The fourth quadrant includes Portugal, Italy, Spain, Slovak Republic, Denmark, each showing the presence of a NDP, a NDP approved before 2003, a national health system, a decreasing mortality trend, and a health expenditure for diabetes <9% of the total national health expenditure. The cloud of points represents the presence of an NDP, health expenditure for diabetes <9%, and the presence of the national health service. The chronicity control system is represented by the chronic care model (CCM), which was developed in the mid-1990s by Wagner [39, 40] . This model covers the needs of health organizations and citizens. The CCM provides six levels of implementation: the organization of care systems with the removal of barriers; self-management with support from a caregiver; support for decisions on prevention or treatment strategies based on medical evidence; delivery of services; a system for recording and monitoring care and community and public health resources [41] . For diabetes mellitus, this means a combination of programs aimed at nutrition education, autonomous control of blood glucose with related strategies, psychological support, and personal empowerment [42] . The growth estimates for diabetes in Europe are quite clear-an increase from 59.8 million cases in 2015 to 71.1 million cases in 2040 [1]. These data are even more alarming in light of the recent SARS-Cov2 pandemic, posing a problem to healthcare stakeholders. In fact, diabetics are more susceptible to lower respiratory tract infections due to the abnormal neutrophil function induced by hyperglycemia [43] . Data from clinical studies show the increased susceptibility of diabetics affected by atypical pneumonia [44] . In this context, the enhancement of telemedicine services appears to be a priority in the control of chronic diseases, especially in lockdown periods. A recent meta-analysis has shown that telemedicine for diabetes treatment is cost effective for both retinal screening and telemonitoring [45] . Another work highlights how the control of the diabetic via telematics allows better control of glycated hemoglobin [46] , which is the main marker of diabetes progression [47] . An important aspect to consider is the organization of diabetes services. The economic crisis of the period 2008-2013 severely tested the health systems of individual countries, with progressive cuts to some services or increases in copayment quotas. Some health systems, by virtue of their organization or recent reform, have been able to cope with these new economic scenarios, while others have found themselves in more difficulty; the effects of the recent economic crisis are still fully visible in terms of mortality trends [48] . The close associations between the organizational and financial aspects can be deduced from the distribution of the variables obtained from the analysis of the reports. In fact, it is clear that the activation of a National Diabetes Plan can contribute to the reduction of the prevalence of mortality from DM and the containment of the global costs of diabetes. Our results show that in countries where there is a national health system (UK, Italy, Spain, Portugal) or an insurance system with high social protection (The Netherlands, France), excellent performance is noted in the control of diabetic disease and its comorbidities. In fact, the guarantee of access to therapies and control and prevention of complications contribute to reducing mortality, while at the same time lead to significant savings. These results are most evident in countries where a national diabetes control plan has been in place for at least 15 years. Another aspect that emerges from our analysis is the care setting. In fact, it seems that the management of diabetes by practitioners compared to diabetic centers guarantees better results in terms of the prevalence of and mortality from T2DM, as underlined by the aforementioned meta-analysis of Gupta et al. [26] . Access to care or better delivery of care represents one of the cornerstones of the CCM model. In our opinion, a similar system should also cover obese individuals by actively involving them in prevention policies, emphasizing self-care by self-management [49] . Our data show that obesity and being overweight are closely related to physical inactivity, especially in females, representing a gender gap. An emphasis on this theme was noted for the women's football world championship [50] . Countries should make greater efforts to guarantee women access to sports activities, promoting the removal of sociocultural barriers and with ad hoc investments; for example, it has been shown that quality public transport and travel infrastructure for pedestrians could reduce the gender gap, allowing women to practice physical activity with greater ease and accessibility [51] . This is a fundamental aspect, especially in light of the fact that physical inactivity is one of the determinants of non-communicable diseases [52] and one of the main determinants of the increase in BMI, and therefore of obesity [50] . In fact, it has been estimated that by 2050, in EU-28 countries obesity will reduce life expectancy rates from 0.9 to 4.2 years and that 8.4% of health budgets will be used to treat complications associated with obesity. Moreover, the consequent economic effects of obesity directly reduce productive activities [51, 53] . In conclusion, 50% of EU 28 countries show type 2 DM prevalence rates in the range of 8-9%. In addition, 21 of the EU-28 countries show a high percentage of overweight, while 7% of EU-28 countries have an obesity prevalence rate of 25%. The record for physical inactivity belongs to Malta. In general, physical inactivity rates are higher for females than males. Regarding care organizations, national public insurance is present in 57% of countries. Diabetes treatment is entrusted to general practitioners in most countries. The results of this work highlight the differences between countries, but also between genders. The patterns identified could indicate cultural and gender trends to which future public health interventions should be addressed. Greater attention should be given to the fight against risk factors for non-communicable diseases, particularly diabetes, considering its high prevalence. This must be a priority for citizens at higher risk. The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. 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   key: cord-276256-gmlsoo2z authors: Avilés-Santa, M. Larissa; Monroig-Rivera, Alberto; Soto-Soto, Alvin; Lindberg, Nangel M. title: Current State of Diabetes Mellitus Prevalence, Awareness, Treatment, and Control in Latin America: Challenges and Innovative Solutions to Improve Health Outcomes Across the Continent date: 2020-10-10 journal: Curr Diab Rep DOI: 10.1007/s11892-020-01341-9 sha: doc_id: 276256 cord_uid: gmlsoo2z PURPOSE OF REVIEW: Latin America is the scenario of great inequalities where about 32 million human beings live with diabetes. Through this review, we aimed at describing the current state of the prevalence, awareness, treatment, and control of diabetes mellitus and completion of selected guidelines of care across Latin America and identify opportunities to advance research that promotes better health outcomes. RECENT FINDINGS: The prevalence of diabetes mellitus has been consistently increasing across the region, with some variation: higher prevalence in Mexico, Haiti, and Puerto Rico and lower in Colombia, Ecuador, Dominican Republic, Peru, and Uruguay. Prevalence assessment methods vary, and potentially underestimating the real number of persons with diabetes. Diabetes unawareness varies widely, with up to 50% of persons with diabetes who do not know they may have the disease. Glycemic, blood pressure, and LDL-C control and completion of guidelines to prevent microvascular complications are not consistently assessed across studies, and the achievement of control goals is suboptimal. On the other hand, multiple interventions, point-of-care/rapid assessment tools, and alternative models of health care delivery have been proposed and tested throughout Latin America. SUMMARY: The prevalence of diabetes mellitus continues to rise across Latin America, and the number of those with the disease may be underestimated. However, some local governments are embedding more comprehensive diabetes assessments in their local national surveys. Clinicians and public health advocates in the region have proposed and initiated various multi-level interventions to address this enormous challenge in the region. Within the last couple of decades, non-communicable diseases (NCDs) have gained worldwide attention, especially in low-and middle-income countries (LMIC), where they have been increasingly recognized and prevalent [1, 2] . Among the NCDs, diabetes mellitus has become a global health challenge [1, 3, 4] . Type 2 diabetes mellitus-the most common form of diabetes-due to its rather silent disruption may be a current uninvited companion to over 465 million persons worldwide. In 2019, it was estimated that the number of persons with diabetes in Latin America (LatAm) was 31.6 million [5, 6] and is predicted that by 2030, the number will increase to 40.2 million, and to 49.1 million by 2045 [6] . Because of its multi-organ and multi-system impact, diabetes has been associated with both acute and long-term complications that affect not only health care needs and costs but also wellbeing and productivity [7, 8] . Within the last decade, it has also been recognized as one of the leading causes of death in some LatAm countries [9] [10] [11] [12] [13] [14] [15] and an important risk factor This article is part of the Topical Collection on Diabetes Epidemiology for cardiovascular diseases (CVD), which is the leading cause of death in LatAm [14, 16] . Far from being a monolithic group, the LatAm population is highly heterogeneous, with various populations reflecting diverse genetic ancestry, ethnicity, culture of origin, sociopolitical contexts, environmental exposures, and beliefs and practices [17, 18] . Levels of inequality in LatAm remain among the highest in the world [19] [20] [21] [22] . All these factorscoupled with biological susceptibility, income, education, access health care, cultural influences on nutrition, health, selfimage, and self-care-influence the development of diabetes in LatAm. We conducted a review of the most current publications on the state of prevalence, awareness, treatment, and control of diabetes mellitus across LatAm. By laying out a detailed accounting of what is known, we aim to identify population, clinical, and health care needs, and opportunities for future research studies and potential interventions. We conducted the search using the PubMed electronic database as the primary scientific literature source. LatAm was defined as the countries in the Western hemisphere which were previously colonized by Spain, Portugal, or France. A combination of keywords was used to define the scope of the searches: diabetes prevalence, awareness, treatment, control, guidelines of care, adherence, retinopathy, nephropathy, neuropathy, foot care, fundoscopic exam, and urine albumin, and searched under LatAm and by each individual country. Hispanics/Latinos living in the USA were not included in the search. We limited the search to publications since 2000 to reflect the most recent research on the prevalence of diabetes across LatAm countries, assessments of awareness, treatment, and control of diabetes (glycemic control), blood pressure and low-density lipoprotein cholesterol (LDL-C), and adherence to guidelines for care recommended by the American Diabetes Association (ADA) [23] [24] [25] and the Latin American Diabetes Association (ALAD) [26] , and specifically hemoglobin A1c (HbA1c) measurement, fundoscopic exam, foot exam, and urine albumin excretion test. We included literature written in English, Spanish, French, and Portuguese. In addition to PubMed, when available, we manually searched each country's Ministry of Health and the Pan American Health Organization (PAHO) websites and accessed published and downloadable national health surveys performed during the selected timeframe. Since most available studies did not distinguish between type 1 and type 2 diabetes mellitus, our review is centered on diabetes mellitus (diabetes, henceforth) in general. Because their specific mechanisms of disease and clinical implications, gestational diabetes mellitus, and type 1 diabetes merit separate reviews. The earliest contemporary reports on the prevalence of diabetes mellitus among adults throughout LatAm date from the 1950s and 1960s [27] [28] [29] , when most countries were beginning to experience epidemiologic transitions [30, 31] . In 2001, Barceló reported an incidence of type 1 diabetes in LatAm in the range 0.1 cases/100,000 in Venezuela to 17.4 cases/ 100,000 in Puerto Rico [32] . However, the authors highlighted a handful of reports on the prevalence of type 2 diabetes and underlined the near absence of surveillance for the disease throughout the LatAm region [32] . From 2005 to 2020, the prevalence of diabetes mellitus across LatAm has been assessed within individual countries and through multinational studies and ranged between 3 and 36.3% (Fig. 1, Table 1 ). In our review, some national surveys assessed the prevalence of diabetes via population representative samples [33, 36, 38, 40, 42-44, 47, 49, 55, 60, 61, 65, 66, 68, 72, 85-87, 89, 91, 96, 98, 105, 107] and used similar population sampling methods (e.g., multi-stage, clustered, probabilistic sampling), whereas other studies focused on specific geographic regions or communities [34, 35, 37, 45, 46, 48-54, 56-58, 63, 67, 73-75, 77, 82-84, 92-95, 102, 110-112] , recruited participants from clinical settings [51, 59, 62, 69, 95] , or focused on specific age groups [37, 42, 56-58, 75, 109, 112] . Also, the age range of the population surveyed-and consequently, age-adjustment estimates-varied among surveys. Most of the studies (especially national surveys) reported the overall prevalence of diabetes without differentiating between type 1 and type 2 diabetes mellitus and many estimated the prevalence of the disease based on selfreport (being aware of having diabetes and/or taking antihyperglycemic medications) only. Some national surveys and independent studies estimated the prevalence based on the sum of self-report and identifying individuals without history of diabetes but hyperglycemia within the diabetes range [26, 115] . The latter group was considered to have "suspected," "undiagnosed," or "unknown" diabetes. Hyperglycemia within the diabetes range was assessed by measuring fasting blood or plasma glucose (FBG or FPG) only, FBG/FPG and 2-h oral glucose tolerance test (OGTT), FBG/FPG and hemoglobin A1c (HbA1c), HbA1c only, or the combination of FBG/FPG, OGTT, and HbA1c, or glucose levels in urine. Some studies measured capillary blood glucose (CBG), while most studies measured venous blood or plasma glucose. While multiple studies used the ADA/ALAD-recommended glucose/HbA1c cut points for the diagnosis of diabetes [26, 115] , some studies used different thresholds (e.g., fasting glucose ≥ 100 mg/dL (per CBG), random blood glucose ≥ 140 mg/dL, or random blood glucose ≥ 200 mg/dL). Although the differences in the methodology described above limit the ability to perform cross-sectional or trend comparisons among countries, we note several commonalities. During 2005-2020, some countries reported an increase in the prevalence of diabetes [33, 36, 38-40, 66, 70-72, 79, 85, 86] , consistent with previously published reviews [5, 15, 32, [116] [117] [118] [119] [120] [121] [122] [123] . Compared with the rest of the region, and as previously reported [5, 15, 32, 124, 125] , diabetes prevalence varies across the region, with higher prevalence in Mexico (13.7%), Haiti (14.1% in women and 8.2% in men), and Puerto Rico (12.5-12.7% in the population aged 18 ≥ years and 26.8% in the population aged ≥ 45 years), and lower in Colombia (3.0% in the population aged 18 ≥ years, but 11.2% in age group ≥ 60 years), Dominican Republic (3.5%), Ecuador (2.7%), Peru (3.7%), and Uruguay (5.5-6.0%) (Fig. 1, Table 1 ). Multiple studies reported a greater prevalence of diabetes among women [36, 38, 40, 42, 44, 47, 49-52, 57, 60, 62, 63, 65, 70, 72, 75, 78, 79, 83-86, 90, 95, 96, 110, 113] , and with increasing age, especially over age 60 years [33, 36, 44, 47, 50, 55, 69-72, 78, 80, 81, 86, 91, 93, 110] . Some studies reported an inverse relationship between diabetes and socioeconomic status (SES) [33, 79, 103] or educational attainment [33, 44, 62, 63, 70, 72, 73, 75, 76, 78, 79, 86, 101] . Other studies reported a direct relationship between having health insurance and self-reported diabetes [42, 70, 97, 100] , implying that persons who have health insurance-proxy of access to health care services-would be aware of their health issues and report them accordingly. This interaction also poses questions about not only the access to health care but also the timeliness and quality of the care, and health literacy (or the lack of) that persons in the lowest SES-and at the highest risk of diabetes-would experience. Some studies reported a lower prevalence of diabetes among indigenous populations [35, 48, 74] , with one study proposing that exposure to urbanicity was associated with an increased prevalence of diabetes among some indigenous communities [83] . Indeed, rural to urban migration (or living in rural compared with urban areas) has been associated with increased prevalence or risk of developing diabetes in Peru [126, 127] , and multiple countries reported a lower diabetes prevalence in rural compared with urban settings [33, 39, 47, 60, 65, 89-91, 99, 103] . The number of epidemiological studies published since 2005 indicates greater public health awareness about diabetes mellitus across LatAm. Multiple countries have performed at least one national survey on chronic non-communicable diseases in which self-reported diabetes mellitus and/or elevated glycemia has been included (Table 1) . Some surveys have also included at least one laboratory test (i.e., fasting or random blood glucose measurement or HbA1c), which could identify individuals at risk of developing diabetes or those who may have it and are not aware of it. Because hyperglycemia may be mediated by at least two mechanisms of disease-increased hepatic glucose output manifested as fasting hyperglycemia and uncoupled postprandial insulin secretion manifested as postprandial hyperglycemia [115, 128] -a single blood test or measurement may not identify all or most of individuals affected by the disease [115] . Therefore, the actual prevalence of diabetes may still be underestimated in many countries, as highlighted in previous reviews [5, 15, 124] . The etiologies of diabetes mellitus are complex. Thus, the increasing prevalence of diabetes experienced across LatAm may reflect the convergence or interaction of multiple factors [18, 125, 129] . For instance, the increasing prevalence of overweight and obesity documented across LatAm has paralleled the increasing prevalence of diabetes in the region [84, 125, 130, 131] . In addition to increased adiposity, type 2 diabetes mellitus and insulin resistance have also been linked to malnutrition (at different life stages) in some LMICs [130, [132] [133] [134] . Stress associated with chronic poverty, intergenerational poverty, natural disasters, and other adverse events [1, 129, 132, 135] has been linked to chronic systemic inflammation and epigenetic changes, potential common denominators of multiple NCDs [136, 137] . Many LatAm major cities may be epicenters where a fragile built environment and infrastructure and changes in lifestyle and nutrition intersect increasing the cumulative risk of developing diabetes in low-income communities [30, 126, 127, 129, 135, 138, 139] . Increased life expectancy has been associated with increased diabetes prevalence [4, 16, 30, 125, 140] , whereas higher educational attainment, increased access to health care, and higher health literacy level are associated with increased awareness of the disease [117] . These are all factors to consider upon designing comprehensive diabetes prevention and treatment strategies across LatAm countries. In addition, the growing prevalence of diabetes mellitus across LatAm and the complexity of the disease suggest opportunities to create or strengthen collaborations towards its prevention and early detection [141] [142] [143] [144] . For example, multinational and multidisciplinary researchpublic health-health care policy-clinical care partnerships which already exist in formal or informal platforms may be well-positioned to evaluate the impact of nutrition, health insurance, housing, and other public policies [79, 141, 143, [145] [146] [147] [148] [149] [150] [151] [152] [153] [154] on health outcomes and assess their potential translation into preventive strategies at the public health and clinical care levels. At the same time, the eventual implementation of such strategies will be strengthened by local governments' commitment to prioritize the prevention and treatment of NCDs, in this case, diabetes, as previously voiced by experts and advocates in the region [79, 141, [155] [156] [157] [158] . Diabetes Awareness, Treatment, and Control Although fewer than studies focused on prevalence, a considerable number of reports centered on diabetes awareness, treatment, and control across LatAm were published between 2005 and 2020 ( 185, 189] . Most studies did not use the term "diabetes awareness," but equated it (or more appropriately, diabetes unawareness) to "suspected," "undiagnosed," "unknown," or "new" diabetes or "elevated glycemia." "Undiagnosed" diabetes-a proxy for lack of diabetes awareness-ranged widely from 10.3 to 50% across studies and countries ( Table 2 ). The prevalence of undiagnosed diabetes was higher in Guatemala (48.8%), Uruguay (48.7%), Puerto Rico (37.7-50%), Honduras (31.9-53.7% range), Mexico (29.9-50% range), and Nicaragua (43.3%) and lower in Colombia (Bogota) (23.5%), the southernmost countries of South America (20.2%), and Costa Rica (10.3-28.4%). Irazola et al. [189] described that diabetes awareness slightly increased with educational attainment. However, associations between undiagnosed diabetes with age, sex, educational attainment, SES, or geographic location were not published by most studies. The observed range of undiagnosed diabetes suggests that the actual prevalence of diabetes across LatAm could exceed previous estimates [6, 124] and that a potentially significant proportion of persons with diabetes for whom both macroand microvascular complications may be present but not assessed and treated. Therefore, current estimates of the prevalence of diabetes across continents may not fully account for the necessary resources to provide adequate health care for Latin Americans with diabetes [7, 8, 190, 191] . Considering the workforce and resources needed to screen the millions of persons across the region who are at risk of diabetes or have the disease and are not aware, experts have proposed diabetes predictive models requiring specific easily obtained clinical data points that could be readily used in primary care settings [192] [193] [194] . Also, the Finnish Diabetes Risk Score (FINDRISC) has been proposed, tested, or modified to screen and identify individuals at high risk of developing diabetes in Latin America [195] [196] [197] [198] [199] . Point-of-care tests for HbA1c and urine microalbumin have also been proposed as alternatives to identify persons with "undiagnosed diabetes" and/or those at risk of chronic kidney disease (CKD) in low-resource and remote settings in LatAm [200] [201] [202] [203] . The standardization, reliability, and repeatability of some of these tests, as well as the clinical and public health benefit derived from their integration into the health care systems, may need to be determined [204] . However, these and other emerging diagnostic technologies [205, 206] are promising alternatives that could be incorporated to assess the prevalence of diabetes and implement timely interventions. The percent of persons with diabetes following any treatment for diabetes ranged from 52.6 to 99% across studies ( Table 2 ). Prescription and/or use of antihyperglycemic medications was mostly assessed via interviews, although a few studies evaluated medical records. Most individuals reported taking oral antihyperglycemic medications either as monotherapy or as a combination of oral medications, while a smaller percent reported using insulin alone or in combination with oral medications. Five (5%) to 12.9% only followed diet/exercise prescription [161, 163, 167, 176, 179, 186] , and 3.2 to 10.1% were not taking any medications [41, 104, 168, 169, 175] . Receiving or adhering to pharmacological treatment was positively associated with having health insurance [71], and receiving medical care in private rather than public health care settings [71, 187] . At least one study observed better pharmacologic treatment adherence with female sex [185] . Achievement of ADA/ALAD-recommended glycemic goals [23, 207] was assessed by multiple studies. The percentage of persons attaining HbA1c < 7% ranged from 3.5 to 54%. However, some studies defined glycemic control based on fasting or random blood glucose thresholds and reported attainment of glycemic control in the 31.4 to 61.4% range. Attainment of glycemic control was associated with higher socioeconomic status (SES) [160] , having health insurance [160] , and better access and services [208] . Not attaining glycemic control was associated with longer duration of diabetes [163, 187, 209] , taking insulin (alone or in combination with oral antihyperglycemic medications) [176] , forgetfulness (e.g., taking multiple medication for more than one condition) [185] , complex therapeutic regimes [209] , inadequate access to health care services [22] , and availability or health insurance coverage of medications [187] , among other factors. In addition to glycemic control, a smaller number of studies examined the attainment of ADA/ALADrecommended blood pressure and LDL-C-blood pressure < 130/80 mmHg and LDL-C < 100 mg/dL-for patients with diabetes [24, 207] . The percentage achieving blood pressure goals ranged from 25 to 67%, and the percent achieving LDL-C goals ranged from 12 to 52.6% Table 2 ). The percent achieving optimal glycemic, blood pressure, and LDL-C levels altogether was reported by a handful of studies and up to 9.9% ( Table 2) . The findings described above denote critical aspects of the state of diabetes care in Latin America. The achievement of glycemic goals reported by the studies included in our review is similar to previously published studies [164, 179, 180, 187, 210] . This implies seriously chronic and inadequate glycemic control at the population level across the region. The inclusion of questions on treatment for glycemic control, medical, and self-care in some national surveys increases our understanding of health-seeking behaviors, both patients' and clinicians' adherence to recommended guidelines of care, and challenges related to the utilization of health care services and availability of medications. The smaller number of studies reporting on the attainment of blood pressure and LDL-C goals and the proportion of patients achieving those goals also poses questions about the prevention of macrovascular complications in persons with diabetes in Latin America, considering the raising prevalence of CVD in the region [16, 211] . Of note, most national surveys report prevalence and treatment and/or control of diabetes, hypertension, and blood cholesterol and the prevalence of tobacco use individually. Since diabetes involves multiple organs and deserves a holistic care approach, reporting on the co-existence of other CV risk factors with diabetes would enhance critical understanding of CV risk and health care needs. Also, some surveys collected biospecimens, but the test results were not included in the reports. It is possible that they are analyzed and published later. Yet including test results in the surveys would offer a more comprehensive picture of the status of diabetes prevention and care needs [180, 212, 213] to plan interventions accordingly. Various studies included in our review reported on participants' receiving or following ADA/ALAD-recommended guidelines of care [25] for early detection and prevention of microvascular disease-annual fundoscopic exam, examination for peripheral neuropathy and comprehensive foot examination, annual function/urine albumin excretion testing, and HbA1c tested at least 3 times per years [38-40, 72, 96, 159, 160, 165, 166, 168, 169, 171, 172, 175, 176, 180, 182, 186, 214] (Table 3) . Some studies assessed the completion of several guidelines, whereas most studies focused on a few. The completion of the selected ADA guidelines varied, ranging from 14.7 to 97.5% for the foot exam, from 8.6 to 92% for the fundoscopic exam, and from 1.1 to 51.1% for the urine albumin excretion test. Most studies (especially national surveys) inquired about having HbA1c checked within the previous 12 months. The affirmative response ranged from 3.7 to 90.0%. In addition to inquiring about HbA1c testing, some surveys asked whether the participant's blood glucose had been tested (by a health care professional). Having private health insurance was associated with a greater number of affirmative responses to the latter [70, 71, 91] . Despite the smaller number of studies evaluating the completion of the ADA guidelines for foot care and prevention of microvascular disease, and the varied guideline completion rates previously described (Table 3) , the prevalence of long-term microvascular complications associated with diabetes has been documented across LatAm. For instance, in the studies included on our review and others published during the same time frame, the rate of foot ulcers ranged from 1.2 to 14.8% [40, [214] [215] [216] , and nontraumatic lower extremity amputations attributable to diabetes ranges from 1.2 to 7.3% [40, 184, 214, 215, [217] [218] [219] [220] [221] , and the prevalence of diabetic retinopathy ranged from 11.2 to 48% [40, 184, 214, 222, 223] . CKD has become a major public health concern across Central America [224] [225] [226] , and the increasing prevalence of diabetes could exacerbate the incidence of CKD-and eventually end-stage renal disease and its associated health complications-in the region [227] [228] [229] . The findings described above underline not just the urgent need to prevent diabetes but also to prevent complications among those with established disease, and the potentially underestimated burden on patients, societies, and health care systems across LatAm. In this regard, several innovative models of health care for patients with diabetes have been proposed and tested throughout LatAm. Combining care of diabetes and other chronic conditions would be expected to maximize time and resources and improve health outcome. Although combining diabetes and chronic pulmonary disease care did not demonstrate a difference in outcomes [230] , this model could be revisited. Also, interventions at the health care system element of the chronic care model might need to be adapted to the local health care system [231] or synchronized with interventions at other levels. Improvement of health care system structure and processes [232] would assure timely access to patient information and enhance clinician decisionmaking. Integrating social determinants of health into diabetes care demonstrated objective improvements in patient knowledge and cardiometabolic parameters [233] . Enhancing medical continuing education [234] , an intervention combining diabetes prevention and self-management [235] , co-creating interventions with community stakeholders and other countries [141, 144] are other examples of alternatives to improve diabetes care throughout the region. Another major regional example of efforts to implement better care for patients with [147] , telehealth, mobile clinics, and other non-traditional health care delivery models. In addition, a non-exhaustive list of examples of past or current interventions, policies, and initiatives is provided in Table 4 [184, 186, 234, [236] [237] [238] [239] [240] [241] [242] [243] [244] [245] [246] [247] [248] [249] [250] [251] [252] . Interventions in the list include tele-ophthalmology [249, 250, 253, 254] , teambased foot self-care education [236] , diabetic retinopathy education and screening at a community pharmacy [255] , rapid assessment/diagnostic tools to screen for or detect retinopathy, nephropathy, and risk of developing foot ulcers [201, [256] [257] [258] [259] [260] [261] [262] and are examples of clinical research and/or implementation activities designed to strengthen the prevention and early detection of diabetes-associated complications and improve health outcomes throughout LatAm. Many interventions on diabetes care have focused on patients and/or clinicians as the primary recipients or enablers of the interventions. Because of the complex nature of the disease and the multiple factors that mediate treatment effectiveness, interventions involving other levels or elements within the health care organization or system [155, 157, 232, [263] [264] [265] or the health care workforce [158, 263, 266] could be considered. Interventions involving other sectors (e.g., housing, infrastructure, national or local policies) could uncover very valuable and needed strategies to enhance treatment effectiveness and potentially reduce health care costs in the long-term. The feasibility and sustainability of such research efforts-and subsequent policies-would need to be demonstrated and supported locally [143] . Multiple studies in our review reported a higher prevalence of diabetes among women [36, 38, 40, 42, 44, 47, 49-52, 57, 60, 62, 63, 65, 70, 72, 75, 78, 79, 83-86, 90, 95, 96, 110, 113] . While the mediating factors for this sex difference need further study (e.g., history of GDM, which was outside of the scope of this review), the increased prevalence of diabetes among women in some LatAm countries would be expected to have implications for health and health care, and potentially future generations [267] [268] [269] . Since diabetes may increase women's risk for CVD, including stroke [270] , cognitive decline [271, 272] , or some cancers [273, 274] , timely and comprehensive preventive care for women of all ages would need to be prioritized. Due to the epidemiologic transition already experienced by some countries throughout LatAm, the population pyramid is also shifting towards a greater proportion of older adults. Studies included in our review consistently reported an increased prevalence of diabetes with age. Diabetes care challenges specific to this age group include risk of obesity or undernutrition [42, 56] , increased risk for disability [57] , economic barriers to appropriate access to health care [42] , disruption in funding of health insurance [275] , disparate completion of diabetes care guidelines based on health insurance coverage [276] , inequalities in access to and utilization of health care services [277] [278] [279] , complex medical care needs and frailty [280] , cultural beliefs, mental health, and lack of family or social support [281] , among others. Prevention of diabetes and its complications and reliable continuity of care and social support [282] need to be especially tailored for this population across the region. A few studies in our review reported a low prevalence of diabetes among some indigenous populations in LatAm [55, 74, 82] , in parallel to some previous reports [283] [284] [285] [286] about other indigenous groups in the region and in contrast with the higher prevalence of diabetes among American Indians in the USA [287] and the First Nations in Canada [288] . However, other studies in our review and in the current literature have documented elevated diabetes prevalence or risk among indigenous and other socioeconomically disadvantaged ethnic groups [48, 50, 73, 76, 77, 83, 90, 91, 166, [289] [290] [291] [292] [293] . Some of the diabetes prevalence studies included in our review focused on or mentioned participants from indigenous groups [35, 48, 50, 74, 83] and other underrepresented groups (e.g., Garifuna, Afro-Panamanian, Afro-Peruvian, Afro-Ecuadorian) [55, 76, 90, 91, 166] . However, a few studies have evaluated diabetes care, prevalence, and/or prevention of macro-or microvascular complications, diabetes management interventions, other health care needs and access to health care among indigenous populations [241, 244, 246, [294] [295] [296] [297] [298] [299] [300] [301] [302] , and none on the other groups (that we could identify through our search). Understanding the protective mechanisms (e.g., biochemical, immune, epigenetic) against diabetes experienced by some indigenous populations would be relevant to millions at high risk of developing diabetes. At the same time, the increased prevalence of the metabolic syndrome and diabetes experienced by some indigenous groups and other ethnic groups may increase their risk not only for CVD and other diabetes long-term complications but also for re-emerging [239] 2 0 0 9 -2011 Mexico, Honduras Interactive Voice Response (IVR) support calls for chronic disease management for Spanish speakers-The investigators report cumulative findings in Honduras, Mexico, and Spanish-speakers in the U.S. Involvement of caregivers enhanced engagement. By self-report, there was improved medication adherence and self-management was similar across sites. Piette, 2011 [240] 2010 Honduras Cloud-Computing Model -The investigators tested a mobile phone-based intervention of weekly VoIP calls and IVR with patients with diabetes and automated emails to clinicians and voicemail reports to family caregivers for six weeks. Improved self-care and diabetes management and significant improvement in glycemic control were reported. Piette, 2016 [241] 2013 Bolivia Structured caregiver feedback -The investigators assessed whether automated telephone feedback to caregivers ("CarePartners") increased engagement in mobile-health support among patients with diabetes and hypertension in Bolivia. Significantly greater engagement was observed. Patients who spoke indigenous languages at home were more than 3X as likely to complete the IVR calls. Piette, 2014 [242] 2013 Bolivia Mobile health program for chronic disease self-management in Bolivia -Assessment and implementation of IVR for 12 weeks. It was associated with improved medication adherence, self-reported health status, and satisfaction. Prestes, 2017 [243] 2 0 1 6 -2017 Argentina DIAPREMintegrated diabetes care program including systemic changes education, registry and disease management Flood, 2016 [244] 2010 Guatemala Implementation and outcomes of a comprehensive type 2 diabetes program in rural Guatemala through a non-government organization and involving nurse-directed care Flood, 2017 [245] 2012 Rural Guatemala Implementation of a multi-level quality improvement program for ambulatory diabetes care based on input from patients and other stakeholders Flood, 2017 [246] 2 0 1 4 -2016 Rural Guatemala Home-based type 2 diabetes self-managementintervention delivered by diabetes educator at home and synchronized with clinic follow-up. Mayan communities Tapia-Conyer, 2016 [247] Gallardo-Rincón, 2017 [234] 2012 to present Mexico CASALUD Model -is a comprehensive primary health care model implemented in Mexico that enables proactive prevention and disease management using innovative technologies and a patient-centered approach. The program was pilot tested in 2009 and implemented nationwide in 2012. infectious diseases, like tuberculosis [303] [304] [305] . Therefore, disease prevention and health care models that account and reach these populations need to be considered. Through this review, we have highlighted the most current reports on prevalence, awareness, treatment, control, and adherence to recommended guidelines of care for diabetes mellitus across LatAm published from 2000 to 2020. During that time frame, a considerable number of surveys assessing the prevalence of the disease and an increasing body of reports on the achievement of treatment and care goals were identified. Such reports demonstrate the imperative need to garner a more comprehensive understanding of the extent of diabetes across countries, and both past and ongoing efforts to establish effective and sustainable models of prevention and high-quality care able to reach and serve all peoples across the region. During the writing of this manuscript, Latin America had been recognized as the new epicenter of the SARS-CoV-2 (COVID-19) pandemic [306] . The effects of the disease in persons with diabetes in the region are beginning to be uncovered [307] [308] [309] , while some solutions are proposed [310, 311] . The magnitude of the impact of the pandemic on the health and health care needs of persons with diabetes mellitus and other NCDs-let alone on the health care systems infrastructures-in the region are yet to be known. 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