LAUSR

Objective To determine predictors of in-hospital mortality related to COVID-19 in older patients. Design Retrospective cohort study. Setting and Participants Patients aged 65 years and older hospitalized for a diagnosis of COVID-19. Methods Data from hospital admission was collected from the electronic medical records. Logistic regression and Cox proportional-hazard models were used to predict mortality, our primary outcome. Variables at hospital admission were categorized according to the following domains: demographics, clinical history, comorbidities, previous treatment, clinical status, vital signs, clinical scales and scores, routine laboratory analysis and imaging results. Results Of a total of 235 Caucasian patients, 43% were male, with a mean age of 86 ± 6.5 years. Seventy-six patients (32%) died. Non-survivors had a shorter number of days from initial symptoms to hospitalization (p=0.007) and the length of stay in acute wards than survivors (p<0.001). Similarly, they had a higher prevalence of heart failure (p=0.044), peripheral artery disease (p=0.009), crackles at clinical status (p<0.001), respiratory rate (p=0.005), oxygen support needs (p<0.001), C-reactive protein (p<0.001), bilateral and peripheral infiltrates on chest radiographs (p=0.001) and a lower prevalence of headache (p=0.009). Furthermore, non-survivors were more often frail (p<0.001), with worse functional status (p<0.001), higher comorbidity burden (p<0.001) and delirium at admission (p=0.007). A multivariable Cox model showed that male sex (HR 4.00, 95% CI 2.08-7.71, p=0.0001), increased fraction of inspired oxygen (HR 1.06, 95% CI 1.03-1.09, p<0.0001) and crackles (HR 2.42, 95% CI 1.15-6.06, p=0.0190) were the best predictors of mortality, while better functional status was protective (HR 0.98, 95% CI 0.97-0.99, p=0.0013). Conclusions and implications In older patients hospitalized for COVID-19 male sex, crackles, a higher fraction of inspired oxygen and functionality were independent risk factors of mortality. These routine parameters, and not differences in age, should be used to evaluate prognosis in older patients.