ABSTRACT
INTRODUCTION: Frailty, a measure of biological aging, has been linked to worse COVID-19 outcomes. However, as the mortality differs across the COVID-19 waves, it is less clear whether a medical record-based electronic frailty index (eFI) that we have previously developed for older adults could be used for risk stratification in hospitalized COVID-19 patients. OBJECTIVES: The aim of the study was to examine the association of frailty with mortality, readmission, and length of stay in older COVID-19 patients and to compare the predictive accuracy of the eFI to other frailty and comorbidity measures. METHODS: This was a retrospective cohort study using electronic health records (EHRs) from nine geriatric clinics in Stockholm, Sweden, comprising 3,980 COVID-19 patients (mean age 81.6 years) admitted between March 2020 and March 2022. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the Clinical Frailty Scale, and the Hospital Frailty Risk Score. Comorbidity was measured using the Charlson Comorbidity Index. We analyzed in-hospital mortality and 30-day readmission using logistic regression, 30-day and 6-month mortality using Cox regression, and the length of stay using linear regression. Predictive accuracy of the logistic regression and Cox models was evaluated by area under the receiver operating characteristic curve (AUC) and Harrell's C-statistic, respectively. RESULTS: Across the study period, the in-hospital mortality rate decreased from 13.9% in the first wave to 3.6% in the latest (Omicron) wave. Controlling for age and sex, a 10% increment in the eFI was significantly associated with higher risks of in-hospital mortality (odds ratio = 2.95; 95% confidence interval = 2.42-3.62), 30-day mortality (hazard ratio [HR] = 2.39; 2.08-2.74), 6-month mortality (HR = 2.29; 2.04-2.56), and a longer length of stay (ß-coefficient = 2.00; 1.65-2.34) but not with 30-day readmission. The association between the eFI and in-hospital mortality remained robust across the waves, even after the vaccination rollout. Among all measures, the eFI had the best discrimination for in-hospital (AUC = 0.780), 30-day (Harrell's C = 0.733), and 6-month mortality (Harrell's C = 0.719). CONCLUSION: An eFI based on routinely collected EHRs can be applied in identifying high-risk older COVID-19 patients during the continuing pandemic.
ABSTRACT
OBJECTIVE: To describe temporal changes in treatment, care, and short-term mortality outcomes of geriatric patients during the first wave of the COVID-19 pandemic. DESIGN: Observational study. SETTING AND PARTICIPANTS: Altogether 1785 patients diagnosed with COVID-19 and 6744 hospitalized for non-COVID-19 causes at 7 geriatric clinics in Stockholm from March 6 to July 31, 2020, were included. METHODS: Across admission month, patient vital signs and pharmacological treatment in relationship to risk for in-hospital death were analyzed using the Poisson regression model. Incidence rates (IRs) and incidence rate ratios (IRRs) of death are presented. RESULTS: In patients with COVID-19, the IR of mortality were 27%, 17%, 10%, 8%, and 2% from March to July, respectively, after standardization for demographics and vital signs. Compared with patients admitted in March, the risk of in-hospital death decreased by 29% [IRR 0.71, 95% confidence interval (CI) 0.51-0.99] in April, 61% (0.39, 0.26-0.58) in May, 68% (0.32, 0.19-0.55) in June, and 86% (0.14, 0.03-0.58) in July. The proportion of patients admitted for geriatric care with oxygen saturation <90% decreased from 13% to 1%, which partly explains the improvement of COVID-19 patient survival. In non-COVID-19 patients during the pandemic, mortality rates remained relatively stable (IR 1.3%-2.3%). Compared with non-COVID-19 geriatric patients, the IRR of death declined from 11 times higher (IRR 11.7, 95% CI 6.11-22.3) to 1.6 times (2.61, 0.50-13.7) between March and July in patients with COVID-19. CONCLUSIONS AND IMPLICATIONS: Mortality risk in geriatric patients from the Stockholm region declined over time throughout the first pandemic wave of COVID-19. The improved survival rate over time was only partly related to improvement in saturation status at the admission of the patients hospitalized later throughout the pandemic. Lower incidence during the later months could have led to less severe hospitalized cases driving down mortality.