Associations between cardiometabolic disease severity, social determinants of health (SDoH), and poor COVID-19 outcomes.

ABSTRACT:

Objective

This study aimed to determine the ability of retrospective cardiometabolic disease staging (CMDS) and social determinants of health (SDoH) to predict COVID-19 outcomes.

Methods

Individual and neighborhood SDoH and CMDS clinical parameters (BMI, glucose, blood pressure, high-density lipoprotein, triglycerides), collected up to 3 years prior to a positive COVID-19 test, were extracted from the electronic medical record. Bayesian logistic regression was used to model CMDS and SDoH to predict subsequent hospitalization, intensive care unit (ICU) admission, and mortality, and whether adding SDoH to the CMDS model improved prediction was investigated. Models were cross validated, and areas under the curve (AUC) were compared.

Results

A total of 2,873 patients were

SUBMITTER: Howell CR 

PROVIDER: S-EPMC9088642 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature