Prospective validation of a dynamic prognostic model for identifying COVID-19 patients at high risk of rapid deterioration.

ABSTRACT:

Background

We sought to develop and prospectively validate a dynamic model that incorporates changes in biomarkers to predict rapid clinical deterioration in patients hospitalized for COVID-19.

Methods

We established a retrospective cohort of hospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 using electronic health records (EHR) from a large integrated care delivery network in Massachusetts including >40 facilities from March to November 2020. A total of 71 factors, including time-varying vital signs and laboratory findings during hospitalization were screened. We used elastic net regression and tree-based scan statistics for variable selection to predict rapid deterioration, defined as progression by two levels of a published severity scale in the next

SUBMITTER: Lin KJ 

PROVIDER: S-EPMC9877647 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature