Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure.

ABSTRACT:

Importance

Traditional models for predicting in-hospital mortality for patients with heart failure (HF) have used logistic regression and do not account for social determinants of health (SDOH).

Objective

To develop and validate novel machine learning (ML) models for HF mortality that incorporate SDOH.

Design, setting, and participants

This retrospective study used the data from the Get With The Guidelines-Heart Failure (GWTG-HF) registry to identify HF hospitalizations between January 1, 2010, and December 31, 2020. The study included patients with acute decompensated HF who were hospitalized at the GWTG-HF participating centers during the study period. Data analysis was performed January 6, 2021, to April 26, 2022. External validation was performed in the hospitaliz

SUBMITTER: Segar MW 

PROVIDER: S-EPMC9260645 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature