Two Years with COVID-19: The Electronic Frailty Index Identifies High-Risk Patients in the Stockholm GeroCovid Study

Abstract

<b><i>Introduction:</i></b> 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. <b><i>Objectives:</i></b> 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. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> 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 (β-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). <b><i>Conclusion:</i></b> An eFI based on routinely collected EHRs can be applied in identifying high-risk older COVID-19 patients during the continuing pandemic.

Automated frailty scores: towards clinical implementation

“…The Swedish eFI is constructed using 48 items from disease diagnoses (ICD-10 codes), signs and symptoms (e.g., activity limitation, sensory impairment, previous falls, incontinence, oral health), and laboratory and anthropometric measures (e.g., blood pressure, hemoglobin, body mass index) ( Figure 1 ). As expected, the Swedish eFI is strongly associated with mortality outcomes [ 5 ] and also has value in risk stratification in COVID-19 patients [ 6 ]. For instance, compared to relatively robust patients (eFI ≤0.15), severely frail patients (eFI >0.25) had 32.8 times higher odds of in-hospital mortality (95% confidence interval [CI] 14.7–93.3), 9.8 times higher risk of 30-day mortality (95% CI 7.3–13.2), and 5.8 times higher risk of 6-month mortality (95% CI 5.0–6.8) after adjusting for age and sex [ 5 ].…”

“…Thirdly, the eFI is flexible such that a variety of deficit items available in the EHR can be incorporated in it, as long as the items cover a wide range of physiological systems (i.e., adhering to the multidimensional nature of the deficit accumulation model) (Figure 1). It is also generalizable to several patient groups, including COVID-19 patients [ 6 ].…”

Health progression for Covid-19 survivors hospitalized in geriatric clinics in Sweden

“…Third, in this analysis, most of the Covid-19 patients with readmission after three months had their 1 st admission during the 1 st two pandemic waves in which e.g. the prognosis of the geriatric Covid-19 patients was worse than in the later waves [ 29 ]. Therefore, Covid-19-related late effects need to be explored in geriatric patients with more later follow-up data.…”

Effect of Age, Sex, and COVID-19 Vaccination History on All-Cause Mortality: Unexpected Outcomes in a Complex Biological and Social System

“…There are so many potential factors from certain medical conditions through to occupational exposure, racial, genetic, frailty functional status factors [190][191][192][193][194][195][196][197][198][199][200]. A combined score based on genetic and clinical risk gave enhanced prediction of severe COVID-19 infection [200].…”

“…Individuals with other risk factors such as occupational exposure, immune suppressing drugs, obesity, kidney disease, Vitamin D deficiency, frailty etc. [190][191][192][193][194][195][196][197][198][199], are advised to be vaccinated or else take other protective measures. As mentioned earlier specific diseases are associated with altered miRNA profiles.…”