Latent class analysis of hospitalization, ICU admission, and mortality among COVID-19 patients in Iran.

ABSTRACT: Identifying COVID-19 patients' clinical phenotypes based on characteristics and comorbidities, as well as their differences, helps in terms of clinical care and potential crises. Our goal is to use Latent Class Analysis (LCA) to identify COVID-19 patient profiles based on demographics, symptoms, and comorbidities, and evaluate their correlation with ICU admission, hospitalization duration, and mortality in a cross-sectional study. We included hospitalized patients with positive SARS-CoV-2 tests in two referral hospitals in the south of Iran between January 2020 and July 2021. Data from 7,968 patients were evaluated in two time-specific intervals, known as "stratum," based on the point at which the COVID-19 fourth peak and vaccinations were nearly initiated. After applying LCA, three classe

SUBMITTER: Ranjbar M 

PROVIDER: S-EPMC11519344 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature