Multimorbidity Patterns and Their Relationship With ICU Admission and Mortality Rates in Hospitalized Patients With COVID-19 in Northern Iran - Maysam Rezapour; Narges Khanjani; Rahim Sharafkhani; Mahmood Moosazadeh (Gonabad University of Medical Sciences, 2024)
Background: Classifying COVID-19 hospitalized patients based on multimorbidity could aid in individual evaluation and provide effective triage for better treatment and management. The aim of this study was to extract multimorbidity patterns among hospitalized COVID-19 patients and determine their associations with admission to intensive care units (ICU) and mortality.  Methods: The data in this retrospective study were acquired from the registry system for all 13,960 COVID-19 patients from 42 hospitals in Mazandaran Province in northern Iran between March 20, 2020, and July 20, 2021. The multimorbidity patterns of 11 chronic diseases were extracted using latent class analysis (LCA). The association between multimorbidity patterns and mortality from COVID-19 and admission to the ICU was examined using multilevel logistic regression modeling.  Results: Four classes were identified, including diabetes and cardiovascular disease (class 1, 3.7%), metabolic diseases and others (class 2, 0.6 %), diabetes and hypertension (class 3, 23.0%), and non-multimorbidity (class 4, 72.7%). Membership in class 1 (diabetes and cardiovascular disease) and class 3 (diabetes and hypertension), compared with class 4 (non-multimorbidity), was associated with higher odds of experiencing death (OR=2.66 for class 1 and 1.21 for class 3). Class 2 did not show a significant difference from class 4 regarding mortality. Conclusion: Multimorbidity classification is a key predictor of COVID-19 patient prognosis, guiding treatment decisions and prioritizing protective measures, such as vaccination. Notably, those with multimorbidity patterns of "diabetes and cardiovascular diseases" and "diabetes and hypertension" exhibit the highest risk of ICU admission and mortality.