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

• Published in: PloS one Vol. 18; no. 8; p. e0290969
• Main Authors: Lleal, Marina, Corral-Vazquez, Celia, Baré, Montserrat, Comet, Ricard, Herranz, Susana, Baigorri, Francisco, Gimeno-Miguel, Antonio, Raurich, Maria, Fortià, Cristina, Navarro, Marta, Poblador-Plou, Beatriz, Baré, Marisa
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 31.08.2023; Public Library of Science (PLoS)
• Subjects: Age; Analysis; Biology and Life Sciences; Bivariate analysis; Cardiovascular diseases; Chronic conditions; Chronic infection; Chronic obstructive pulmonary disease; Cluster analysis; Comorbidity; COVID-19; Diabetes mellitus; Disease susceptibility; Health aspects; Infection; Medical research; Medicine and Health Sciences; Medicine, Experimental; Morbidity; Mortality; Risk factors; Sex; Spain; Spain
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0290969

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. 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. Severe infection was reported in 9.5% (95% CI: 9.0-9.9) of the patients, and death occurred in 3.9% (95% CI: 3.6-4.2). We identified multimorbidity clusters related to severity/mortality in most age groups from 21 to 65 years. In males, the cluster with highest percentage of severity/mortality was Heart-liver-gastrointestinal (81-90 years, 34.1% severity, 29.5% mortality). In females, the clusters with the highest percentage of severity/mortality were Diabetes-cardiovascular (81-95 years, 22.5% severity) and Psychogeriatric (81-95 years, 16.0% mortality). This study characterized several multimorbidity clusters in COVID-19 patients based on sex and age, some of which were found to be associated with higher rates of infection severity/mortality, particularly in younger individuals. Further research is encouraged to ascertain the role of specific multimorbidity patterns on infection prognosis and identify the most vulnerable morbidity profiles in the community.