Archives of Academic Emergency Medicine. 2020; 8(1): e35 REV I EW ART I C L E Prevalence of Underlying Diseases in Hospitalized Pa- tients with COVID-19: a Systematic Review and Meta- Analysis Amir Emami1∗, Fatemeh Javanmardi1, Neda Pirbonyeh1, Ali Akbari2 1. Microbiology Department, Burn and Wound Healing Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. 2. Department of Anesthesiology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran. Received: March 2020; Accepted: March 2020; Published online: 24 March 2020 Abstract: Introduction: In the beginning of 2020, an unexpected outbreak due to a new corona virus made the head- lines all over the world. Exponential growth in the number of those affected makes this virus such a threat. The current meta-analysis aimed to estimate the prevalence of underlying disorders in hospitalized COVID-19 pa- tients. Methods: A comprehensive systematic search was performed on PubMed, Scopus, Web of science, and Google scholar, to find articles published until 15 February 2020. All relevant articles that reported clinical char- acteristics and epidemiological information of hospitalized COVID-19 patients were included in the analysis. Results: The data of 76993 patients presented in 10 articles were included in this study. According to the meta- analysis, the pooled prevalence of hypertension, cardiovascular disease, smoking history and diabetes in people infected with SARS-CoV-2 were estimated as 16.37% (95%CI: 10.15%-23.65%), 12.11% (95%CI 4.40%-22.75%), 7.63% (95%CI 3.83%-12.43%) and 7.87% (95%CI 6.57%-9.28%), respectively. Conclusion: According to the find- ings of the present study, hypertension, cardiovascular diseases, diabetes mellitus, smoking, chronic obstructive pulmonary disease (COPD), malignancy, and chronic kidney disease were among the most prevalent underlying diseases among hospitalized COVID-19 patients, respectively. Keywords: Comorbidity; COVID-19; severe acute respiratory syndrome coronavirus 2; Meta-analysis Cite this article as: Emami A, Javanmardi F, Pirbonyeh N, Akbari A. Prevalence of Underlying Diseases in Hospitalized Patients with COVID- 19: a Systematic Review and Meta-Analysis. Arch Acad Emerg Mede. 2020; 8(1): e35. 1. Introduction In late 2019, a novel corona virus (first: 2019-nCov, then: SARS-CoV-2) was identified as the cause of a cluster of pneu- monia cases, which infected a lot of people in Wuhan, a city in the Hubei province of China (1). SARS-CoV-2 rapidly spread and led to an outbreak in China and then became a global health emergency. Although control measures and isolations have been applied for prevention, the infection has increased and caused a pandemic (2). Although this virus belongs to a relatively well-known viral family, Coronaviri- dae, and is similar to viruses that caused severe acute res- piratory syndrome (SARS), which had an outbreak in 2002, and Middle East respiratory syndrome (MERS), which had ∗Corresponding Author: Amir Emami; Microbiology Department, Burn and Wound Healing Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. Email: emami.microbia@gmail.com, Tel: +98-71-3230 5884 an outbreak in 2012, in some characteristics, there are a lot of uncertainties and unknown specifications about this virus such as its origin and source of infection, its emergence, and its mechanism of action and transmission (3, 4). Since the number of COVID-2019 cases is rising around the world and it has been associated with a large number of mortality and morbidity, it has led to a new global phobia called Coro pho- bia (5). Based on recent reports, the novel Corona virus can be identified through various symptoms (Fever, Cough, Dys- pnea, Myalgia, and Fatigue) (6-8). Similar to other viral respiratory infections, SARS-CoV-2 or COVID-19 can be transmitted through the respiratory tract. It mainly causes respiratory tract infections and develops se- vere pneumonia in infected patients who may require inten- sive care. Severe disease may result in death due to progres- sive respiratory failure (9, 10). Everyone is susceptible to this virus, but the elderly and those with underlying diseases are more at risk of adverse outcomes. Current knowledge has shown that death rate is high in people with chronic underly- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Emami et al. 2 ing diseases (11). Therefore, special attention should be paid to the elderly and immunocompromised patients. Infections might progress rapidly in these groups and timely clinical decisions are needed (12). Currently, information on the prevalence of predominant chronic diseases is rare. More- over, knowing the underlying diseases in COVID-19 infected patients is important for healthcare workers. In the current study, a systematic review and meta-analysis was conducted on the prevalence of underlying diseases in confirmed hos- pitalized COVID-19 cases. 2. Methods 2.1. Search Strategy In order to find relevant studies, international databases in- cluding PubMed, Scopus, Web of Science, Google scholar, and Embase were searched for articles published until 16 February 2020. The following search terms were used (de- signed using English MeSH keywords and Emtree terms): [SARS-CoV-2 AND characteristics] OR , [2019-nCoV AND Characteristics]" OR "COVID-19 AND Comorbidities] OR [new coronavirus AND Characteristics AND Comorbidities] OR [Wuhan Coronavirus AND Characteristics AND Comor- bidities] OR [Coronavirus AND characteristics AND Comor- bidities]. Additionally, extra searches were performed in the reference lists of included studies to avoid missing papers. Moreover Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) portals as the na- tional public health institute were evaluated. Due to the huge number of articles in Chinese language, the abstracts were evaluated in these studies. 2.2. Inclusion and Exclusion Criteria Any relevant articles that reported clinical characteristics and epidemiological information on infected patients were in- cluded in the analysis. All articles with any design (ran- domized controlled trials, non-randomized controlled trials, case-control studies, cross-sectional studies) were included. Articles were excluded if appropriate information was not re- ported. 2.3. Data extraction and paper quality evalua- tion Two authors (A.E. and F.J.) screened and evaluated the liter- ature independently. All the included papers were assessed using the Newcastle-Ottawa Scale and the results are pro- vided in table 1 (13). The following features were extracted for pooled estimation: name of the first authors and age, sex, and coexisting condition of the patients. 2.4. Statistical analysis Overall prevalence with 95% confidence interval was esti- mated via inverse variance method. Heterogeneity was eval- uated using chi-square and I2. The random effect model was used in case of considerable heterogeneity, which was de- fined as I2>75%. Sensitivity analysis was done according to outlier data. Egger’s regression test was used to evaluate pub- lication biases. All statistical analyses were performed using STATA 13, metaprop command. 3. Results 3.1. Characteristics of included studies In the initial search, 1250 articles were found in different databases. All papers were screened by reading their ab- stracts and 289 of them were eliminated due to being dupli- cates found in different databases. After evaluating the full texts, 804 studies were excluded due to presenting data that were irrelevant to our aim. 10 articles met the inclusion cri- teria but some of the required information was not reported in all of the articles. Figure1 shows the search details, and the characteristics of included studies are provided in table 2. Fi- nally, the available data of 3,403 hospitalized patients with COVID-19 infection were used for the analysis. 3.2. Prevalence of underlying diseases in hospi- talized COVID-19 cases - Hypertension Through the current meta-analysis, it was found that hyper- tension is the most prevalent underlying disease in hospital- ized COVID-19 cases. 16% (95%: CI: 10.15%-23.65%) of SARS- CoV-2 infected cases were hypertensive (figure 2). This infor- mation was reported in 7 studies. According to the I2 index, which was calculated to be 86.42%, and the Chi-square re- sults, there was high and significant heterogeneity between the studies (P<0.001). No publication bias was found in stud- ies (t= -1.67, P=0.15). In addition, the corresponding funnel plot is provided in figure 3. Cardiovascular disease In order to estimate the pooled prevalence of cardiovascu- lar disease in COVID-19 patients, 8 studies were evaluated. The incidence was 12.11% (95%CI: 4.40% – 22.75%), with high and significant heterogeneity (I2=95.89%), also no pub- lication bias was present according to Eggers’s test (t= 1.99, p=0.09). The funnel plot has been shown in figure 3. Sensi- tivity analysis did not show significant changes. Smoking In the forest plot drawn (Figure 4), the pooled prevalence of SARS-CoV-2 infection in hospitalized patients with history of smoking was estimated as 7.63 percent. High and significant heterogeneity was found between the 6 included studies (I2= This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 3 Archives of Academic Emergency Medicine. 2020; 8(1): e35 90.19%, p < 0.001). Moreover, no publication bias was found (t= -0.24, p=0.82). It is worth noting that the number of smok- ers in Wenhua Liang’s study was calculated using the infor- mation presented in the study (14). - Diabetes mellitus Us- ing the data of 6 included articles, the prevalence of diabetes among people who were infected with SARS-CoV-2 was esti- mated to be 7.87% (95%CI: 6.57% âĂŞ 9.28%), which is pre- sented in figure 5. No publication bias was present based on Egger’s test and the funnel plot presented in figure 3 (t=-1.64, p=0.17). Chronic kidney disease As shown in figure 6, the pooled prevalence of acute kidney diseases in SARS-CoV-2 hospitalized patients was estimated as 0.83% (95% CI: 0.37%- 1.43%). A fixed model was used for meta-analysis of data presented in 7 included studies. No publication bias was present according to Egger’s test and the related funnel plot presented in figure 3 (t=1.83, p=0.12) Malignancy The pooled prevalence of malignancy among hospitalized COVID-19 patients was estimated to be 0.92% (95% CI: 0.56%-1.34%) (results presented in 7 articles, Figure 7). In this section, a fixed effect analysis was used. The value of t in Eg- ger’s test was 1.14 and the p-value was 0.305, which means that no publication bias was present. The related funnel plot is depicted in figure 3. Chronic obstructive pulmonary diseases (COPD) The last comorbidity that was studied using the included ar- ticles was chronic obstructive pulmonary diseases (COPD). According to our statistical analysis, the incidence rate of COPD in hospitalized COVID-19 patients was 0.95% (95% CI: 0.43%-1.61%). Although there were many articles about this new Coronavirus, this coexisting disorder was reported in only 5 published studies. In order to evaluate the pooled prevalence, a fixed model was used and the results are shown in Figure 8. The value of t in Egger’s test was found to be 1.81 and the p-value was 0.16, which means that no publication bias was present. The related funnel plot is shown in figure 3. 4. Discussion China and the rest of the world have faced an outbreak of a novel Corona virus. The widespread distribution of this virus has led to a major concern, globally. Human coron- aviruses are among the pathogens causing viral respiratory infections, and the recently detected strain called SARS-CoV- 2 has caused a big challenge for countries all over the world (15, 16). This is the third contagious Coronavirus leading to an epidemic in the 21st century after MERS and SARS (17). The key problems surrounding this novel virus are as follows: diagnosis, mode of transmission, long incubation period (3 to 14 days), predicting the number of infected cases in the community, and insufficient protection resources due to its pandemic specification (15, 18). The accurate transmission rate of SARS-CoV-2 is unknown, since various factors impact its transmission. Moreover, infection of family clusters and healthcare workers indicate the human to human transmis- sion of the disease and its contagiousness, which makes the condition more complicated (19, 20). Since SARS-CoV-2 is a newly identified pathogen, there is no pre-existing immunity to it in the human community, also there is no definitive cure to interrupt or reduce its aston- ishing spread. These ambiguities make the condition more serious for vulnerable members of the community, which include individuals with immune problems, co-existing co- morbidity and elderly people. Despite the novelty of the topic, there are a lot of proposed studies about history, trans- mission route, urgency of responding, pathogenic potential characteristics and prevention strategies but there are still some underlying diseases that have remained unknown (21). According to the current analysis, hypertension, cardio- vascular diseases, diabetes, kidney disease, smoking, and COPDs were among the most prevalent underlying diseases among hospitalized patients with COVID-19. In terms of pre-existing medical conditions, cardiovascular diseases had the highest prevalence among diseases that put patients at higher risk of SARS-CoV-2 threats. Decreasing the pro- inflammatory cytokines, which leads to a weaker immune function may account for this condition (2, 22). It is worth noting that similar results were found regarding MERS (23). We also found that smokers are more susceptible to Coron- avirus infections, especially to the most recent species. Var- ious reasons may justify this happening. It has been men- tioned that smokers have unregulated ACE2 in remodeled cell types, which is consistent with results of SARS studies. However, factors such as amount of smoking, the duration of smoking, and the duration of smoking cessation also play a role. In some previous studies on MERS-CoV-2 it has been shown that dipeptidyl peptidase IV (DPP4), which is the spe- cific receptor for this virus, had a higher rate of expression in smokers and COPD patients (24). Although the results of the current analysis indicate that smoking can be an underlying factor that makes people sus- ceptible to COVID-19 complications, in some studies, espe- cially COVID-19 related studies, no strong evidence has been found regarding the correlation of COPD and smoking with being infected with this new virus. But the important point that must be taken into consideration is that the outcome of SARS-CoV-2 infection is more severe in COPD cases and smokers (25). As mentioned in the results section, patients with malig- nancies are more in danger than those without any tumor. Anticancer treatments such as chemotherapy and surgery put this group into an immunosuppressive state and subse- quently at higher risk of MERS-CoV-2 infection (26). Among This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Emami et al. 4 those with malignancies, lung cancer patients seems to be more susceptible, and they must follow guidance on restrict- ing any contact with possible infected zones or individuals for their safety (14). Possible risk factors for progressive and severe illness may include the above-mentioned factors but are not limited to them; pregnancy and old age are other risky conditions, which should be monitored meticulously. However, there is no clear evidence about the risk of transmission of COVID-19 to the newborn during vaginal delivery or transmission via breastfeeding but care and protection of newborns against possible exposure to infection or contaminated conditions such as maternal breast contamination must be observed. Since MERS-CoV-2 is an emerging virus, no specific treat- ment is currently available (27, 28), and pathophysiology of this condition is still unknown. Therefore, general prevention measures such as the following should be followed: Wash- ing hands frequently and avoiding touching the eyes, nose, and mouth with contaminated hands, avoiding close contact ,especially with those who have fever, coughing or sneezing, avoiding contact with live animals and consuming raw ani- mal products (29). There are some responsibilities for health policymakers in this critical condition: Screening of travelers, triage all pa- tients on admission and immediately isolating all suspected and confirmed cases, providing protective gear, preparing lo- cal guidance and instructions for people, especially for high risk groups (30, 31). To the best of our knowledge, this is the first meta-analysis that estimates the prevalence of underly- ing diseases in patients infected with SARS-CoV-2. Given that most studies on CoVID-19 are in an early stage, and there are some limitations such as small number of studies, and reports being restricted to China and a few other countries, due to the pandemic nature of the disease, specific patterns should be introduced for different groups, including people with underlying diseases, to minimize the harm. Based on the experiences gained on this disease during this short time, a strong recommendation for all people, clini- cians, and policymakers is to guide people to protect them- selves to avoid being exposed to SARS-CoV-2, whenever pos- sible (32). Another very important advice to patients with un- derlying diseases during the epidemics like the one caused by the novel virus is to follow guidance on travel restrictions. These groups must be aware of their high-risk situation and comply with all health guidelines such as hand hygiene, face care, and restricting social interactions. In addition, to re- duce the morbidity and complications of COVID-19 in differ- ent populations, especially patients with the mentioned un- derlying diseases, we recommend clinicians and policymak- ers to launch diagnostic procedures for such individuals first so that proper treatments can be designed and followed to ensure they are protected within epidemic regions (33). In summary, the results of the current study have shown that in patients with SARS-CoV-2 infection, hypertension, cardio- vascular disease, smoking, and diabetes are the most preva- lent co-existing disorders. Given that COVID-19 has a rel- atively long incubation period and during this time the in- fected person can transmit the virus without showing symp- toms, it is strongly recommended that patients with chronic or underlying diseases avoid any close contact with other people in the community, especially in epidemic areas. Dur- ing the current SARS-CoV-2 pandemic, the statistics reported by different countries regarding associated mortality of those with risk factors, incubation time, and estimated overall mortality have not been consistent and general conclusions should be drawn with caution. It should be noted that the outbreak worsens with decrease in adherence to diagnostic guidelines and prevention strategies, such as avoiding travel- ing and gathering in public places. 5. Conclusion According to the findings of the present study, hypertension, cardiovascular diseases, diabetes mellitus, smoking, COPD, malignancy, and chronic kidney disease were among the most prevalent underlying diseases among hospitalized pa- tients with COVID-19, respectively. 6. Declarations 6.1. Acknowledgements All the authors thank the Vice chancellor of Research, Shi- raz University of Medical Sciences, for their cooperation for obtaining the approval of the ethical committee (Code: IR.SUMS.REC.1398.1379). 6.2. Authors Contributions A.E designed the study, searched the database, extracted the data and did the quality assessment. F. J did the statistical analysis and wrote the results section, and assessed the quality of studies. A. E and F. J wrote the initial draft and N.P and A.K revised and edited the paper. Authors ORCIDs Amir Emami: 0000-0002-4510-1820 Fatemeh Javanmardi: 0000-0001-8841-0861 Neda Pirbonyeh: 0000-0001-5700-3913 Ali Akbari: 0000-0002-2970-2052 6.3. Funding Support None. 6.4. Conflict of Interest All authors declare that they have no conflict of interest. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 5 Archives of Academic Emergency Medicine. 2020; 8(1): e35 References 1. Tan W, Zhao X, Ma X, Wang W, Niu P, Xu W, et al. A novel coronavirus genome identified in a cluster of pneumo- nia cases–Wuhan, China 2019– 2020. China CDC Weekly. 2020;2(4):61-2. 2. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epi- demiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet. 2020;395(10223):507-13. 3. Gorbalenya AE. Severe acute respiratory syndrome- related coronavirus-The species and its viruses, a state- ment of the Coronavirus Study Group. BioRxiv. 2020. 4. Liu Y, Yang Y, Zhang C, Huang F, Wang F, Yuan J, et al. 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Downloaded from: http://journals.sbmu.ac.ir/aaem 7 Archives of Academic Emergency Medicine. 2020; 8(1): e35 Table 1: NEWCASTLE-OTTAWA quality assessment scale for cross sectional studies First author, year Selection Comparability Exposure/Outcome Total Score Chaolin Huang, 2020 ***** * *** ********* Nanshan Chen,2020 ***** ** *** ********** Dawei Wang, 2020 ***** ** *** ********** Jie.Li, 2020 ***** ** *** ********** Wei-Jie Guan, 2020 ***** ** *** ********** Xiao-Wei Xu, 2020 ***** * ** ******** Wenhua Liang,2020 ***** * *** ********* Jin-jin Zhang, 2020 ***** ** *** ********** Jian Wu, 2020 ***** ** *** ********** Kui L2020 **** ** *** ********* Table 2: characteristics of included studies First Author n Sex (M/F) Age CKD HTN DM Mal Smoking COPD CVD Chaolin Huang, et al. (34) 41 30/11 Range: 41-58 3 6 8 1 3 1 6 Nanshan Chen, et al. (2) 99 67/32 Mean: 55.5 ±13.1 3 1 2 40 Dawei Wang, et al. (35) 138 78/63 Median: 56 (42-68) 4 43 14 10 4 20 Jie.Li, et al. (36) 17 9/8 Range: 22-65 8 1 3 Wei-Jie Guan, et al. (37) 1099 640/459 Range: 35-58 1 164 81 10 158 12 27 Xiao-Wei Xu, et al. (38) 62 35/27 Median: 41 (32-52) 5 1 1 1 Wenhua Liang,et al. (14) 1590 - - 18 111 Jin-jin Zhang, et al. (16) 140 71/69 Median: 57 (25-87) 2 42 17 9 2 7 Jian Wu, et al. (39) 80 39/41 Mean: 46.1 ± 15.4 1 1 25 Kui L, et al. (40) 137 61/76 Median: 57(20-83) 13 14 2 10 CKD: chronic kidney disease; HTN: hypertension; DM: diabetes mellitus; Mal: malignancy; COPD: chronic obstructive pulmonary diseases; CVD: cardiovascular disorders. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Emami et al. 8 Figure 1: PRISMA flow chart of the systematic literature review and article identification. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 9 Archives of Academic Emergency Medicine. 2020; 8(1): e35 Figure 2: Prevalence of hypertension among patients hospitalized with COVID-19. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Emami et al. 10 Figure 3: Funnel plot for meta-analysis of the prevalence of underlying diseases in COVID-19 infected cases. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 11 Archives of Academic Emergency Medicine. 2020; 8(1): e35 Figure 4: Prevalence of cardiovascular disease among patients hospitalized with COVID-19. Figure 5: Prevalence of smokers among patients hospitalized with COVID-19. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Emami et al. 12 Figure 6: Prevalence of diabetes among patients hospitalized with COVID-19. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 13 Archives of Academic Emergency Medicine. 2020; 8(1): e35 Figure 7: Prevalence of kidney disease among patients hospitalized with COVID-19. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Emami et al. 14 Figure 8: Prevalence of malignancies among patients hospitalized with COVID-19. Figure 9: Prevalence of chronic obstructive pulmonary disease (COPD) among patients hospitalized with COVID-19. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem Introduction Methods Results Discussion Conclusion Declarations References