Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?

ABSTRACT: Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devices capable of detecting short episodes of arrhythmia are now widely available. Although it has recently been suggested that some high-risk patients with AF detected on implantable devices may benefit from anticoagulation, long-term management remains challenging in lower-risk patients and in those with AF detected on monitors or wearable devices as the development of clinically meaningful arrhythmia burden in this group remains unknown. Identification and prediction of clinically relevant AF is therefore of unprecedented importance to the cardiologic community. Family history and underlying genetic markers are important risk factors for AF. R

SUBMITTER: Petzl AM 

PROVIDER: S-EPMC11332604 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature