Frailty and comorbidity in predicting community COVID-19 mortality in the U.K. Biobank: The effect of sampling

Background/objectives: Frailty has been linked to increased risk of COVID-19 mortality, but evidence is mainly limited to hospitalized older individuals. This study aimed to assess and compare predictive abilities of different frailty and comorbidity measures for COVID-19 mortality in a community sample and COVID-19 inpatients.

Design: Population-based cohort study.

Setting: Community.

Participants: We analyzed (i) the full sample of 410,199 U.K. Biobank participants in England, aged 49-86 years, and (ii) a subsample of 2812 COVID-19 inpatients with COVID-19 data from March 1 to November 30, 2020.

Measurements: Frailty was defined using the physical frailty phenotype (PFP), frailty index (FI), and Hospital Frailty Risk Score (HFRS), and comorbidity using the Charlson Comorbidity Index (CCI). PFP and FI were available at baseline, whereas HFRS and CCI were assessed both at baseline and concurrently with the start of the pandemic. Inpatient COVID-19 cases were confirmed by PCR and/or hospital records. COVID-19 mortality was ascertained from death registers.

Results: Overall, 514 individuals died of COVID-19. In the full sample, all frailty and comorbidity measures were associated with higher COVID-19 mortality risk after adjusting for age and sex. However, the associations were stronger for the concurrent versus baseline HFRS and CCI, with odds ratios of 20.40 (95% confidence interval = 16.24-25.63) comparing high (>15) to low (<5) concurrent HFRS risk category and 1.53 (1.48-1.59) per point increase in concurrent CCI. Moreover, only the concurrent HFRS or CCI significantly improved predictive ability of a model including age and sex, yielding areas under the receiver operating characteristic curve (AUC) >0.8. When restricting analyses to COVID-19 inpatients, similar improvement in AUC was not observed.

Conclusion: HFRS and CCI constructed from medical records concurrent with the start of the pandemic can be used in COVID-19 mortality risk stratification at the population level, but they show limited added value in COVID-19 inpatients.