Dynamic modeling of hospitalized COVID-19 patients reveals disease state-dependent risk factors.

ABSTRACT:

Objective

The study sought to investigate the disease state-dependent risk profiles of patient demographics and medical comorbidities associated with adverse outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections.

Materials and methods

A covariate-dependent, continuous-time hidden Markov model with 4 states (moderate, severe, discharged, and deceased) was used to model the dynamic progression of COVID-19 during the course of hospitalization. All model parameters were estimated using the electronic health records of 1362 patients from ProMedica Health System admitted between March 20, 2020 and December 29, 2020 with a positive nasopharyngeal PCR test for SARS-CoV-2. Demographic characteristics, comorbidities, vital signs, and laboratory test resul

SUBMITTER: Soper BC 

PROVIDER: S-EPMC8903413 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature