Real-Time Prediction of Mortality, Cardiac Arrest, and Thromboembolic Complications in Hospitalized Patients With COVID-19.

ABSTRACT:

Background

COVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease.

Objectives

The purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19.

Methods

Retrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's perfo

SUBMITTER: Shade JK 

PROVIDER: S-EPMC9080121 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature