Is Age the Most Important Risk Factor in COVID-19 Patients? The Relevance of Comorbidity Burden: A Retrospective Analysis of 10,551 Hospitalizations

Valero-Bover D. Monterde D. Carot-Sans G. Cainzos-Achirica M. Comin-Colet J. Vela E. Clèries M. Folguera J. Abilleira S. Arrufat M. Lejardi Y. Solans Ò. Dedeu T. Coca M. Pérez-Sust P. Pontes C. Piera-Jiménez J.
2023 Dove Medical Press Ltd

Clinical Epidemiology
2023 #15 811 - 825 pp.

Purpose: To assess the contribution of age and comorbidity to the risk of critical illness in hospitalized COVID-19 patients using increasingly exhaustive tools for measuring comorbidity burden. Patients and Methods: We assessed the effect of age and comorbidity burden in a retrospective, multicenter cohort of patients hospitalized due to COVID-19 in Catalonia (North-East Spain) between March 1, 2020, and January 31, 2022. Vaccinated individuals and those admitted within the first of the six COVID-19 epidemic waves were excluded from the primary analysis but were included in secondary analyses. The primary outcome was critical illness, defined as the need for invasive mechanical ventilation, transfer to the intensive care unit (ICU), or in-hospital death. Explanatory variables included age, sex, and four summary measures of comorbidity burden on admission extracted from three indices: the Charlson index (17 diagnostic group codes), the Elixhauser index and count (31 diagnostic group codes), and the Queralt DxS index (3145 diagnostic group codes). All models were adjusted by wave and center. The proportion of the effect of age attributable to comorbidity burden was assessed using a causal mediation analysis. Results: The primary analysis included 10,551 hospitalizations due to COVID-19; of them, 3632 (34.4%) experienced critical illness. The frequency of critical illness increased with age and comorbidity burden on admission, irrespective of the measure used. In multivariate analyses, the effect size of age decreased with the number of diagnoses considered to estimate comorbidity burden. When adjusting for the Queralt DxS index, age showed a minimal contribution to critical illness; according to the causal mediation analysis, comorbidity burden on admission explained the 98.2% (95% CI 84.1–117.1%) of the observed effect of age on critical illness. Conclusion: Comorbidity burden (when measured exhaustively) explains better than chronological age the increased risk of critical illness observed in patients hospitalized with COVID-19.

case-mix tool , comorbidities , comorbidity burden , COVID-19 , hospitalized patients , risk assessment

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Catalan Health Service, Barcelona, Spain
Digitalization for the Sustainability of the Healthcare System (DS3) – Institut d’Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, Spain
Catalan Institute of Health, Barcelona, Spain
Center for Outcomes Research, Houston Methodist, Houston, TX, United States
Johns Hopkins, Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins Medical Institutions, Baltimore, MD, United States
Cardiology Department, Bellvitge University Hospital (IDIBELL), Barcelona, Spain
Department of Medicine, University of Barcelona, Hospitalet de Llobregat, Barcelona, Spain
CIBER Cardiovascular (CIBERCV), L’Hospitalet de Llobregat, Barcelona, Spain
CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
Health Department, eHealth Unit, Barcelona, Spain
WHO European Centre for Primary Health Care, Almaty, Kazakhstan
Department of Pharmacology, Autonomous University of Barcelona, Barcelona, Spain
Faculty of Informatics, Telecommunications and Multimedia, Universitat Oberta de Catalunya, Barcelona, Spain

Catalan Health Service
Digitalization for the Sustainability of the Healthcare System (DS3) – Institut d’Investigacions Biomèdiques de Bellvitge (IDIBELL)
Catalan Institute of Health
Center for Outcomes Research
Johns Hopkins
Cardiology Department
Department of Medicine
CIBER Cardiovascular (CIBERCV)
CIBER Epidemiología y Salud Pública (CIBERESP)
Health Department
WHO European Centre for Primary Health Care
Department of Pharmacology
Faculty of Informatics

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