Utility of risk prediction models to detect atrial fibrillation in screened participants.

ABSTRACT:

Aims

Atrial fibrillation (AF) is associated with higher risk of stroke. While the prevalence of AF is low in the general population, risk prediction models might identify individuals for selective screening of AF. We aimed to systematically identify and compare the utility of established models to predict prevalent AF.

Methods and results

Systematic search of PubMed and EMBASE for risk prediction models for AF. We adapted established risk prediction models and assessed their predictive performance using data from 2.5M individuals who attended vascular screening clinics in the USA and the UK and in the subset of 1.2M individuals with CHA2DS2-VASc ≥2. We assessed discrimination using area under the receiver operating characteristic (AUROC) curves and agreement between observed

SUBMITTER: Poorthuis MHF 

PROVIDER: S-EPMC8651014 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature