key: cord-310123-h7i49pdb
authors: De Smet, Robert; Mellaerts, Bea; Vandewinckele, Hannelore; Lybeert, Peter; Frans, Eric; Ombelet, Sara; Lemahieu, Wim; Symons, Rolf; Ho, Erwin; Frans, Johan; Smismans, Annick; Laurent, Michaël R.
title: Frailty and mortality in hospitalized older adults with COVID-19: retrospective observational study
date: 2020-06-09
journal: J Am Med Dir Assoc
DOI: 10.1016/j.jamda.2020.06.008
sha: 
doc_id: 310123
cord_uid: h7i49pdb

ABSTRACT Objectives To determine the association between frailty and short-term mortality in older adults hospitalized for coronavirus disease 2019 (COVID-19). Design Retrospective single-center observational study. Setting and participants: N = 81 patients with COVID-19 confirmed by reverse-transcriptase polymerase chain reaction (RT-PCR), at the Geriatrics department of a general hospital in Belgium. Measure ments: Frailty was graded according to the Rockwood Clinical Frailty Scale (CFS). Demographic, biochemical and radiological variables, co-morbidities, symptoms and treatment were extracted from electronic medical records. Results Participants (N = 48 women, 59%) had a median age of 85 years (range 65 – 97 years), median CFS score of 7 (range 2 – 9), and 42 (52%) were long-term care residents. Within six weeks, eighteen patients died. Mortality was significantly but weakly associated with age (Spearman r = 0.241, P = 0.03) and CFS score (r = 0.282, P = 0.011), baseline lactate dehydrogenase (LDH) (r = 0.301, P = 0.009), lymphocyte count (r = -0.262, P = 0.02) and RT-PCR cycle threshold (Ct, r = -0.285, P = 0.015). Mortality was not associated with long-term care residence, dementia, delirium or polypharmacy. In multivariable logistic regression analyses, CFS, LDH and RT-PCR Ct (but not age) remained independently associated with mortality. Both age and frailty had poor specificity to predict survival. A multivariable model combining age, CFS, LDH and viral load significantly predicted survival. Conclusions and implications Although their prognosis is worse, even the oldest and most severely frail patients may benefit from hospitalization for COVID-19, if sufficient resources are available.

Results: Participants (N = 48 women, 59%) had a median age of 85 years (range 65 -97 years), 12 median CFS score of 7 (range 2 -9), and 42 (52%) were long-term care residents. Within six weeks, 13 eighteen patients died. Mortality was significantly but weakly associated with age (Spearman r = 14 0.241, P = 0.03) and CFS score (r = 0.282, P = 0.011), baseline lactate dehydrogenase (LDH) (r = 0.301, 15 P = 0.009), lymphocyte count (r = -0.262, P = 0.02) and RT-PCR cycle threshold (Ct, r = -0.285, P = 16 0.015). Mortality was not associated with long-term care residence, dementia, delirium or 17 polypharmacy. In multivariable logistic regression analyses, CFS, LDH and RT-PCR Ct (but not age) 18 remained independently associated with mortality. Both age and frailty had poor specificity to 19 predict survival. A multivariable model combining age, CFS, LDH and viral load significantly predicted 20 survival. 21

Although their prognosis is worse, even the oldest and most severely 22 frail patients may benefit from hospitalization for COVID-19, if sufficient resources are available. 23

Coronavirus disease 2019 is a global pandemic caused by severe acute respiratory 28 syndrome coronavirus 2 (SARS-CoV-2). 1 Older adults are at increased risk of hospitalization and 29 mortality due to Different ethical guidelines deal with triage in case a surge in hospital admissions due to overwhelms scarce hospital resources. 6-8 Likelihood of benefit, age and frailty are among the most 32 commonly used triage criteria. 9, 10 In the U.K. and in Belgium (among other countries), intensive care 33 unit (ICU) admission is not recommended for frail older adults aged 65 years and older. 11, 12 These 34 guidelines rely on frailty assessment according to the Rockwood Clinical Frailty Scale (CFS). Patients 35 can be classified on the CFS as not frail (scores 1-4), mildly frail (score 5), moderately frail (score 6) or 36 severely frail (score 7-9). 13 ICU admission is discouraged for frail older adults i.e. those with a CFS 37 score of 5 or higher in the U.K. and Belgium. 11, 12 Hospital admission is discouraged for nursing home 38 residents with suspected or confirmed COVID-19 and a CFS score of 7 or higher. 12 39

Previous studies have shown that frailty is associated with worse outcomes in hospitalized older 40 adults. 13, 14 However, little is known about the outcomes in frail older adults or long-term care 41 residents hospitalized for COVID-19. Therefore, the aim of this retrospective observational study was 42 to describe outcomes in hospitalized geriatric COVID-19 patients according to their age, degree of 43 frailty and place of residence. 44

A retrospective, single-center observational study was performed among COVID-19 patients at the 47 Geriatrics Department of our General Hospital in Belgium, admitted between March 12 th and April 48 30 th , 2020. Demographic, clinical, laboratory and radiographic parameters were extracted from 49 electronic health records. Laboratory values included C-reactive protein (CRP, reference values < 5 50 mg/L), ferritin, D-dimers, lactate dehydrogenase (LDH), 25-hydroxyvitamin D levels and white blood 51 cell, platelet and lymphocyte counts. Polypharmacy was defined as the use of five or more 52

Ethics 54

The Ethical Committee approved the research protocol and waived the need for informed consent, 55 since it did not constitute a clinical study according to national and European regulations. 56

Clinical procedures 57 COVID-19 was confirmed by reverse transcriptase polymerase chain reaction (RT-PCR) testing on 58 nasopharyngeal swabs, using protocols validated within our national SARS-CoV-2 reference 59 network. 15 All patients admitted through the emergency department were screened for COVID-19 by 60 low-dose chest computed tomography (CT). Findings on COVID-19 likelihood and extent of 61 pulmonary involvement (CT-score ranging 0 -25) were reported using a standardized radiological 62 protocol as described previously. 15 63

All COVID-19 patients in our hospital were hospitalized on dedicated wards under the care of a staff 64 pulmonologist, nephrologist, infectious disease specialist or geriatrician, depending on their usual 65 care team (e.g. nephrology in dialysis patients). Additional local criteria to admit patients under 66 geriatric care were age 85 years or older, long-term care residence or equivalent home care (i.e. 67 complete dependency on assistance for activities of daily living), patients with dementia or delirium, 68 or patients aged 75 years and older with multiple co-morbidities and polypharmacy. 69

On admission, an experienced geriatrician scored premorbid frailty according to the CFS based on 70 information from patients, their families, caregivers, primary care referral letters or long-term care 71 records. 72

Statistics 73 examined using Mann-Whitney U-test and Chi-square test for continuous and categorical variables, 76 respectively. Association of age, frailty and other baseline characteristics with mortality were 77 evaluated by Spearman r and multiple logistic regression. Survival according to frailty status was 78 examined using odds ratios, survival analyses (log-rank Mantel-Cox test) and receiver-operator curve 79 (ROC) analysis. Two-tailed P values < 0.05 were considered significant. All analyses were performed 80 using GraphPad Prism v8.4.2. 81

Baseline characteristics of our cohort are shown in Table 1 . Median age was 85 years (minimum 65, 83 maximum 97 years), and 48 were women (59%). Median CFS score was 7 (range 2-9). Dementia had 84 been diagnosed in 36 patients (44%), and 42 (52%) were long-term care residents. Polypharmacy was 85 present in 52 (64%) subjects. 86

Sex, place of residence, dementia, polypharmacy, extent of affected lung tissue on CT or CRP values 87 at baseline did not differ between survivors and non-survivors. However, compared to survivors of 88 COVID-19, non-survivors were significantly older (88.5 vs. 85 years, median age) and frailer (median 89 CFS 7 vs. 6). Their RT-PCR cycling threshold (Ct) values were also significantly lower (indicating higher 90 viral load). Baseline LDH was significantly higher and baseline lymphocyte count lower in non-91 survivors. Baseline CRP, ferritin, D-dimer, white blood cell, platelet or 25-hydroxyvitamin D levels 92

were not different (latter data not shown). Lymphopenia was present on admission in 48 patients 93 (60%) and occurred during admission in 60 of 80 patients (75%; one patient was excluded due to 94 chronic lymphocytic leukemia). The peak CRP and lymphocyte nadir reached during admission was 95 higher among non-survivors, and these differences were highly significant. Length of stay tended to 96 be shorter in those who died (P = 0.05). 97

Among these variables, the CFS score was associated with dementia (P < 0.0001, r = 0.602), long-98 term care residence (P < 0.0001, r = 0.465), and weakly with sex (lower frailty in males, P = 0.007, r = 6 -0.296) and incident delirium (P = 0.043, r = 0.230). There was no significant association between CFS 100 and older age in our cohort. 101

One out of seventeen patients died in the non-frail group (CFS score 1-4), compared to eighteen 102 deaths among 64 frail patients, however this difference did not reach significance (P = 0.054). 103 Supplementary Fig. 1A shows survivors and non-survivors according to their age and CFS. Most 104 deaths occurred in older, frailer patients. However, this group overlapped considerably with many 105 surviving frail older patients. Kaplan-Meier curves also showed only a trend towards higher mortality 106 in frail vs. non-frail subjects (Mantel-Cox log-rank P = 0.06, Supplementary Fig. 1B) . 107

Next, we examined the clinical diagnostic utility of the individual variables that were significantly 108 associated with mortality, in multiple logistic regression analyses. Again, age, CFS, RT-PCR Ct values 109 and LDH were significantly associated with higher odds of mortality ( Table 2 and Supplementary Fig.  110 1C-F), whereas baseline lymphocyte count was no longer significant. In a bivariate model with age 111 and CFS score combined, only the CFS remained significantly associated with mortality. The area 112 under the ROC curve (AUROC) was 0.7443 (95% CI 0.6213 -0.8673) for this model (Figure 1A) , with a 113 positive and negative predictive value of 57% and 80%, respectively. When age and CFS were 114 combined with RT-PCR Ct values and LDH the latter three variables remained significantly associated 115 with mortality. The four-factor model predicted probability of mortalilty (range 0-1) as follows 116 (intercept + β1*age + β2*CFS + β3*RT-PCR Ct value + β4*LDH): -13.89 + 0.126*years + 0.561*CFS-117 score + (-0.1623)*Ct + 0.5275*[U/L]/100 (Supplementary Table 1) . The AUROC for this model was 118 0.8824 (0.7384 -1.000, P < 0.0001, Figure 1B) , with a negative predictive power of 89.5% and a 119 positive predictive power of 78%, sensitivity of 54% and specificity of 78%. 120

Seven patients were treated with hydroxychloroquine, 60 (74%) with antibiotics, 46 (57%) with i.v. 121 fluid support and 25 with glucocorticoids (31%). Seven patients were admitted to ICU, five of whom 122 died. The odds ratio for mortality was significantly higher in patients requiring ICU admission (P = admission, incubation time and a local outbreak in one of our non-COVID-19 wards into account). 126

Four of these patients died. There was no significantly higher or lower mortality between presumed 127 hospital-acquired or community-acquired COVID-19 cases. 128

The current COVID-19 pandemic particularly strikes frail older adults and/or long-term care residents, 130 posing considerable medical and ethical challenges for overwhelmed healthcare systems. Different 131 guidelines have been released to assist triage in this population. 9, 11,16 Belgian and U.K. guidelines 132 recommend the CFS to inform decision making regarding hospital referral of nursing homes residents 133 with suspected or confirmed COVID-19. However, empirical evidence supporting the use of frailty 134 instruments to predict treatment outcomes and thus apply triage restrictions, has remained 135 lacking. 17 136

The short-term mortality (~23%) in this case series is similar to mortality rates reported for 137 hospitalized older adults in Wuhan or California, 3, 4 but lower than reported by Sun et al. 18 or than in 138 the New York City area. 2 This may be considered unexpected, given the greater frailty and older age 139 of our patients compared to previous cohorts. Similar or higher mortality rates have been reported in 140 long-term care residents 19 or in younger ICU populations. 20 These findings support the notion that it 141 may be discriminatory and unethical to restrict hospital care based on age or frailty status alone. 10, 21 142

Still, mortality was higher in patients requiring ICU transfer in our cohort, suggesting that intensive 143 care is of unclear clinical benefit in this population. 22 144

Older age was significantly but weakly associated with increased risk of mortality, confirming recent 145 studies. 1-4 Anecdotally, nonagenarians or centenarians have survived Our main finding 146 was that frailty was also significantly but weakly associated with higher risk of mortality in COVID-19 147 patients (multivariate odds ratio for mortality with each higher CFS point: 1.75.) Still, many severely 148 frail patients survived (72%), and the CFS by itself had poor specificity and no useful cut-off for mortality prediction. A recent study from Italy showed that in N=105 COVID-19 patients, frailty as 150 assessed by the fraity index was associated with in-hospital mortality or ICU admission, independent 151 of age and sex. 24 152

Apart from age and frailty, LDH was the only circulating biomarker significantly associated with 153 mortality in our cohort. This confirms prior studies. 25, 26, 27 However, only few patients met this 154 criterion in our cohort, making it practically useless. Maximal CRP and nadir lymphocyte count during 155 admission was significantly associated with mortality, but these parameters are not available at 156 baseline. Interestingly, we observed a significant association between RT-PCR Ct values and 157 mortality. Viral load peaks longer in patients with more severe COVID-19 and in older adults, as 158 shown by Zheng et al. 28 We speculate that higher viral load may also be a marker for increased risk of 159 mortality, although sampling bias needs to be excluded before we can support this conclusion. Of 160 note, our RT-PCR method was semi-quantitative rather than quantitative, precluding extrapolation to 161 other settings. The four-factor model combining clinical, host and viral parameters showed the most 162 promising characteristics, but still remained inadequate from a clinical perspective. Sun et al. 163 reported a similar logistic regression model based on older age and lymphocyte count. 18 Further 164 work is needed to establish optimal clinical, viral and host immune system characteristics to predict 165 mortality among COVID-19 patients. 26 166

Our study provides the geriatric community with several novel insights into the outcomes of frail 167 older COVID-19 patients. However, we recognize several limitations, mainly due to our retrospective 168 study design. Since data were obtained retrospectively from electronic health records, missing data 169 (e.g. for CT-scan or biochemical parameters) may have introduced bias, and follow-up was limited. 170

However, selection bias is unlikely, since we included consecutive cases in a country with universal 171 health coverage. Caution should be applied to extrapolate findings from this single-center study to 172 other healthcare settings. The associations we observed may not be causally related. Despite our 9 underpowered. A larger sample size would have helped reduce the size of our parameter estimate 175 confidence intervals and increase the validity of our model; however the first COVID-19 wave ended 176 in our hospital and no more deaths have accumulated. We chose not to include patients with so-177 called "radiographically confirmed" COVID-19 i.e. with typical clinical features and radiographic 178 evidence on chest CT, but with repeatedly negative SARS-CoV-2 RT-PCR. However, only three such 179 patients were excluded, which is unlikely to have influenced the results. 180

Many instruments to determine frailty are available. 29 We applied the CFS, which has been adopted 181 in several national COVID-19 triage policies, most notably by U.K. NICE guidelines. 11 Previous 182 research has shown that CFS scores can reliably be obtained in critically ill patients based on chart 183 review, patient interview and/or family interview. 30 However, we recommend further research to 184 ascertain the reproducibility and reliability before widespread implementation of the CFS during 185 COVID-19 outbreaks. Importantly, we were unable to include younger, non-frail patients, since frailty 186 was not assessed in non-geriatric patients. The association between frailty and mortality would likely 187 have been stronger if we included younger, less frail patients. 188

In summary, we showed that age and frailty were significantly but weakly associated with mortality 190 among hospitalized older adults affected by COVID-19. However, both frailty and age alone have 191 poor specificity to predict mortality, and many severely frail patients survived COVID-19. We 192 recommend clinicians, ethicists and policy makers to consider these empirical findings. 

COVID-19 and Older Adults: What We 196

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Characteristics of Hospitalized Adults With COVID-201 19 in an Integrated Health Care System in California

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Complementing chronic frailty assessment at hospital 226 admission with an electronic frailty index (FI-Laboratory) comprising routine blood test 227 results

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submillisievert chest CT for the diagnosis of COVID-19

COVID-19: Use of the Clinical Frailty Scale for Critical Care 235

Frailty in the Face of COVID-19

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China: A Retrospective Study

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Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy

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China's Oldest Coronavirus Survivors

Frailty Index Predicts Poor Outcome

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Conflict of interest: MRL has received consultancy and lecture fees from Alexion, Amgen, Kyowa Kirin, Menarini, Sandoz, Takeda, UCB and Will-Pharma, none of which are related to this work. All other authors have no conflicts.Author contributions: RDS and MRL designed the study, collected the data, analyzed the results and wrote the first draft. All authors contributed to the care of our COVID-19 patients, assisted in the data collection and analysis of the results, the writing of the manuscript and approved the final version.
