Multimorbidity patterns in COVID-19 patients and their relationship with infection severity: MRisk-COVID study.

ABSTRACT:

Background

Several chronic conditions have been identified as risk factors for severe COVID-19 infection, yet the implications of multimorbidity need to be explored. The objective of this study was to establish multimorbidity clusters from a cohort of COVID-19 patients and assess their relationship with infection severity/mortality.

Methods

The MRisk-COVID Big Data study included 14 286 COVID-19 patients of the first wave in a Spanish region. The cohort was stratified by age and sex. Multimorbid individuals were subjected to a fuzzy c-means cluster analysis in order to identify multimorbidity clusters within each stratum. Bivariate analyses were performed to assess the relationship between severity/mortality and age, sex, and multimorbidity clusters.

Results

Severe in

SUBMITTER: Lleal M 

PROVIDER: S-EPMC10470964 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature