Age and frailty are independently associated with increased COVID-19 mortality and increased care needs in survivors: results of an international multi-centre study

Abstract

Introduction Increased mortality has been demonstrated in older adults with COVID-19, but the effect of frailty has been unclear. Methods This multi-centre cohort study involved patients aged 18 years and older hospitalised with COVID-19, using routinely collected data. We used Cox regression analysis to assess the impact of age, frailty, and delirium on the risk of inpatient mortality, adjusting for sex, illness severity, inflammation, and co-morbidities. We used ordinal logistic regression analysis to assess the impact of age, Clinical Frailty Scale (CFS), and delirium on risk of increased care requirements on discharge, adjusting for the same variables. Results Data from 5,711 patients from 55 hospitals in 12 countries were included (median age 74, IQR 54–83; 55.2% male). The risk of death increased independently with increasing age (>80 vs 18–49: HR 3.57, CI 2.54–5.02), frailty (CFS 8 vs 1–3: HR 3.03, CI 2.29–4.00) inflammation, renal disease, cardiovascular disease, and cancer, but not delirium. Age, frailty (CFS 7 vs 1–3: OR 7.00, CI 5.27–9.32), delirium, dementia, and mental health diagnoses were all associated with increased risk of higher care needs on discharge. The likelihood of adverse outcomes increased across all grades of CFS from 4 to 9. Conclusions Age and frailty are independently associated with adverse outcomes in COVID-19. Risk of increased care needs was also increased in survivors of COVID-19 with frailty or older age.

Mental disorders and risk of COVID-19-related mortality, hospitalisation, and intensive care unit admission: a systematic review and meta-analysis

“…Sensitivity analyses highlighted an effect of single studies on the overall estimates (appendix 4 pp 37-38). A high proportion of unexplained heterogeneity was identified (OR I²=93•01%, Q=128•76, p<0•0001; aOR I²=89•51%, Q=57•21, p<0•0001), and a subgroup analysis was done to explore whether the diagnostic category explained a Zimering et al (2020) 34 GeMRC (2021) 39 Turk et al (2020) 27 Genet et al (2020) 25 Fond et al (2020) 9 Huls et al (2021) 36 Poblador-Plou et al (2020) 8 Allen et al (2020) 21 Nemani et al (2021) 4 Baillargeon et al (2020) 24 Yang et al (2020) 32 Landes et al (2020) 26 Siso-Almirall et al (2020) 31 Li et al (2020) 30 Reilev et al (2020) 7 Landes et al (2021) 28 Bitan et al (2021) 37 Canal-Riveiro et al (2021) 38 Lee et al (2020) 29 Yanover et al (2020) 33 An et al (2020 proportion of the heterogeneity (appendix 4 pp 39-40). After correction for multiple comparisons, none of the diagnostic categories were found to be consistently associated with an increased risk for ICU admission.…”

Longitudinal Analysis of COVID-19 Patients Shows Age-Associated T Cell Changes Independent of Ongoing Ill-Health

“…While age is known to affect immune recovery in treated chronic infections such as HIV, there is relatively little known about ageing and immune recovery following acute viral infections (35). The ageing immune system has been implicated in the ageingassociated mortality rate in acute COVID-19 (36,37). T cell responses are crucial in modulating the immune response and preventing host damage in acute viral infections such as influenza (38).…”

The Use of Antiviral Agents against SARS-CoV-2: Ineffective or Time and Age Dependent Result? A Retrospective, Observational Study among COVID-19 Older Adults

“…The primary outcome of the study is to investigate whether a timely administration of a combined regimen of HCQ and LPV/r or DVR/c, related to the symptom onset, could improve patients' outcome in terms of mortality. Assuming mortality of 43.5% detected in a previous study on 3191 COVID-19 patients >65 years (prevalence ranges from 33.7% in those between 65 and 80 years to 53.5% in those >80 years) [20], the required sample size to achieve an 80% power (β = 0.2) at α = 0.05 to detect a difference in mortality between early vs. late drug start with 1 to 1 allocation is 154 patients assuming an OR of 2.5, and 110 patients assuming an OR of 3.0 [21]. We performed univariate analyses using the chi-square test for independence for categorical variables and unpaired t-test (or, if assumptions were not met, Mann-Whitney's test) for quantitative variables.…”