Performance of Atrial Fibrillation Risk Prediction Models in Over 4 Million Individuals.

ABSTRACT:

Background

Atrial fibrillation (AF) is associated with increased risks of stroke and heart failure. Electronic health record (EHR)-based AF risk prediction may facilitate efficient deployment of interventions to diagnose or prevent AF altogether.

Methods

We externally validated an electronic health record AF (EHR-AF) score in IBM Explorys Life Sciences, a multi-institutional dataset containing statistically deidentified EHR data for over 21 million individuals (Explorys Dataset). We included individuals with complete AF risk data, ≥2 office visits within 2 years, and no prevalent AF. We compared EHR-AF to existing scores including CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology Atrial Fibrillation), C₂HEST (coronary artery disease or chroni

SUBMITTER: Khurshid S 

PROVIDER: S-EPMC7856013 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature