RT Journal Article
T1 Multimorbidity Profiles and Infection Severity in COVID-19 Population Using Network Analysis in the Andalusian Health Population Database.
A1 Carmona-Pírez, Jonás
A1 Ioakeim-Skoufa, Ignatios
A1 Gimeno-Miguel, Antonio
A1 Poblador-Plou, Beatriz
A1 González-Rubio, Francisca
A1 Muñoyerro-Muñiz, Dolores
A1 Rodríguez-Herrera, Juliana
A1 Goicoechea-Salazar, Juan Antonio
A1 Prados-Torres, Alexandra
A1 Villegas-Portero, Román
K1 COVID-19
K1 chronic diseases
K1 disease burden
K1 multimorbidity
K1 network analysis
K1 severity
AB Identifying the population at risk of COVID-19 infection severity is a priority for clinicians and health systems. Most studies to date have only focused on the effect of specific disorders on infection severity, without considering that patients usually present multiple chronic diseases and that these conditions tend to group together in the form of multimorbidity patterns. In this large-scale epidemiological study, including primary and hospital care information of 166,242 patients with confirmed COVID-19 infection from the Spanish region of Andalusia, we applied network analysis to identify multimorbidity profiles and analyze their impact on the risk of hospitalization and mortality. Our results showed that multimorbidity was a risk factor for COVID-19 severity and that this risk increased with the morbidity burden. Individuals with advanced cardio-metabolic profiles frequently presented the highest infection severity risk in both sexes. The pattern with the highest severity associated in men was present in almost 28.7% of those aged ≥ 80 years and included associations between cardiovascular, respiratory, and metabolic diseases; age-adjusted odds ratio (OR) 95% confidence interval (1.71 (1.44-2.02)). In women, similar patterns were also associated the most with infection severity, in 7% of 65-79-year-olds (1.44 (1.34-1.54)) and in 29% of ≥80-year-olds (1.35 (1.18-1.53)). Patients with mental health patterns also showed one of the highest risks of COVID-19 severity, especially in women. These findings strongly recommend the implementation of personalized approaches to patients with multimorbidity and SARS-CoV-2 infection, especially in the population with high morbidity burden.
YR 2022
FD 2022-03-23
LK http://hdl.handle.net/10668/21050
UL http://hdl.handle.net/10668/21050
LA en
DS RISalud
RD Apr 5, 2025