key: cord-290836-jldfrec9
authors: Laosa, Olga; Pedraza, Laura; Álvarez-Bustos, Alejandro; Carnicero, Jose A.; Rodriguez-Artalejo, Fernando; Rodriguez-Mañas, Leocadio
title: Rapid assessment at hospital admission of mortality risk from COVID-19: the role of functional status
date: 2020-10-08
journal: J Am Med Dir Assoc
DOI: 10.1016/j.jamda.2020.10.002
sha: 
doc_id: 290836
cord_uid: jldfrec9

Objective To evaluate the role of functional status along with other used clinical factors on the occurrence of death in patients hospitalized with COVID-19. Design Prospective Cohort study Setting Public University Hospital (Madrid) Participants and methods 375 consecutive patients with COVID-19 infection, admitted to a Public University Hospital (Madrid) between March 1 and March 31, 2020, were included in the Prospective Cohort study. Death was the main outcome. The main variable was disability in Activities of Daily Living (ADL) assessed with the Barthel index. Covariates included sex, age, severity index (Quick Sequential Organ Failure Assessment, qSOFA), polypharmacy (>5 drugs in the month before admission), and comorbidity (≥3 diseases). Multivariable logistic regression was used to identify risk factors for adverse outcomes. Estimated model coefficients served to calculate the expected probability of death for a selected combination of five variables: Barthel, sex, age, comorbidities and severity index (qSOFA). Results Mean age was 66 years (SD 15.33), 207 (55%) males. 74 patients died (19.8%). Mortality was associated to low Barthel index (OR per 5-point decrease 1.11; 95CI 1.03-1.20), male sex (0.23, 0.11-0.47), age (1.07, 1.03-1.10) and comorbidity (2.15; 1.08-4.30) but not to qSOFA (1.29, 0.87-1.93) or polypharmacy (1.54; 0.77-3.08). Calculated mortality risk ranged from 0 to 0.78. Conclusions and implications Functional status predicts death in hospitalized COVID-19 patients. Combination of five variables allows to predict individual probability of death. These findings provide useful information for the decision-making process and management of patients.

In December 2019, the first case of SARS-CoV-2 infection was reported in Wuhan, 30 China 1 , resulting in an outbreak that was declared a pandemic on 11 March 2020 by 31 the World Health Organization (WHO) 2 . COVID-19 pandemic has had a major impact in 32 the Madrid region, where 27509 cases and 3603 deaths were registered on the same 33 date (31 March 2020, the last date of inclusion in our study) 3 . Regarding age 34 distribution, 86% of deaths have occurred in patients over 70 years of age and 95% if 35 we extend to those over 60 years. Mortality reaches over 60% for patients over 80 36 years 4 . Taking this fact into account, it should be expected that relevant factors 37 associated to mortality in older people, like functional status [5] [6] [7] [8] , had been included in 38 predictive models of coronavirus mortality. However, this has not been the case, with 39 its potential impact on the decision-making process 9 . 40 Deterioration of functional status, as a sign of an augmented vulnerability state and a 41 declining of biological reserves, is generally considered a strong predictor of poor 42 outcome mainly, but not exclusively, in older people 7, 10, 11 . Often frailty and disability, 43 rather than illness, have significant prognostic value 5 . In fact, frailty predicts mortality 44 in older people independently from other clinical variables [12] [13] [14] [15] . 45 The role of functional status in determining poor outcomes in old patients with COVID- 46 19 has not been yet firmly established. Evidence is even smaller regarding the joint 47 Therefore, the aim of this study was to evaluate, in patients hospitalized with COVID- 50 19, the role of limitations in activities of daily living along with other habitual clinical 51 factors on death during hospitalization, building a predictive model.

We analyzed the data of a cohort comprising all the COVID-19 patients admitted to a 55 Public University Hospital (Madrid, Spain). We have included patients hospitalized 56 from March 1 to 31, 2020, a time period covering the peak of the pandemics in the 57 Madrid region. All cases were selected consecutively according to the date of 58 admission to hospital, due to COVID-19 infection confirmed by positive PCR.

Information on COVID-19 and the current disease course was collected from hospital 61 electronic clinical records, while information on drug treatment and comorbidities 62 before admission were obtained from electronic primary health-care records.

Main outcome included mortality during hospitalization. We followed patients until 65 discharge, death or June 18, 2020, whichever was first. On June 18, 2020, 2 patients 66 were still in-hospital, and were excluded from the analyses. clinical records. This was not possible in 5 patients, who were excluded from the 73 analyses. Barthel Index score has been split into the following categories: 0-60 (severe 74 disability); 65-85 (moderate disability); 90-95 (mild disability) and 100 (no disability).

We collected data about age, sex and comorbidities (hypertension, diabetes mellitus, 77 obesity, hyperlipidemia, ischemic heart disease, heart failure, atrial fibrillation, 78 thromboembolic disease including deep vein thrombosis and pulmonary embolism, 79 stroke, chronic obstructive pulmonary disease (COPD), asthma, cancer, and chronic 80 kidney disease). To evaluate the number of diseases needed to characterize significant 81 comorbidity we assessed the number of diseases that were associated with increased 82 mortality (Annex , Table A1 ). 83 Clinical severity was assessed with the qSOFA (Quick Sequential [Sepsis-related] Organ 84 Failure Assessment) score which identifies high-risk patients for in-hospital mortality. It 85 includes three clinical criteria, assigning one point for low blood pressure (SBP≤100 86 mmHg), high respiratory rate (≥22 breaths/min), or altered consciousness (Glasgow 87 coma scale<15). The score ranges 0-3 point 18 . 88 The number of drug treatments in the month preceding the current hospitalization 89 was also collected. Patients were classified in two groups: with (≥ 5 drugs) or without 90 (< 5 drugs) polypharmacy. 104 We performed two sensitivity analysis. We repeated the analysis excluding patients 105 younger than 40 years, among whom deaths were not observed. The second one 106 regarded the calculated expected probability of death, including the severity (i.e., 107 qSOFA) of the clinical status of the patient. 108 The level of significance was set at p<.05. The analyses were performed using the 109 statistical package R for windows (version 3.6.1). March 2020) 19 .

The study included 375 patients with a mean age of 66 years (SD 15.33), 207 males 116 (55.2%) ( Table 1 ). The median number of comorbidities was 2 (Interquartile range IQR 117 J o u r n a l P r e -p r o o f [1] [2] [3] [4] . 74 patients died (19.7%), and 299 (79.7%) recovered and were discharged before 118 the end of the follow-up. Differences between the two groups were statistically 119 significant for all the morbidities analyzed except for obesity, thromboembolic disease, 120 and asthma. 121 The median number of morbidities in those who died was 4 (IQR 2-5) while in those 122 who survived was 2 (IQR 0-3). Differences in the Barthel Index between groups were 123 statistically significant (p <.001). 124 When we looked at qSOFA, 21.67% of patients who died presented at least 2 criteria of 125 severity (median 1) versus 10.45% in the group of patients who recovered (median 0) 126 (p=0.043). 127 In logistic regression analysis, a 5-point lower in the Barthel score was associated with 128 a 13% increased risk of death Table A2 ). 137 We developed a model to predict the risk of death in males (Annex , Table A3 ) and (Tables 3, 4 ), so we show this "expanded" 142 model. Risk of mortality ranged 0% to 78%. The association between disability and risk 143 of death showed a dose-dependent relationship. While mild disability (Barthel 90-95) 144 increases the risk moderately, it does in a very significant way when it was moderate 145 or severe, especially in older people. 146 The main results held in the sensitivity analysis excluding patients younger than 40 147 years (Annex , Table A5 ).

In this study we show that, in addition to other variables usually considered, functional 150 status is an independent risk factor for death. Barthel index remained associated to 151 the risk of death in all the models developed in our study, with a mean increase of 10-152 15% in the risk of death by each decrease of 5-points. This finding expands those 153 recently reported in a multicenter study about the effect of frailty on mortality 13 . 154 The presence of comorbidity, defined as having ≥3 comorbidities, was associated to an 155 increased risk of mortality, like in many other publications [20] [21] [22] 

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