Detection of Left Atrial Myopathy Using Artificial Intelligence-Enabled Electrocardiography.

ABSTRACT:

Background

Left atrial (LA) myopathy is common in patients with heart failure and preserved ejection fraction and leads to the development of atrial fibrillation (AF). We investigated whether the likelihood of LA remodeling, LA dysfunction, altered hemodynamics, and risk for incident AF could be identified from a single 12-lead ECG using a novel artificial intelligence (AI)-enabled ECG analysis.

Methods

Patients with heart failure and preserved ejection fraction (n=613) underwent AI-enabled ECG analysis, echocardiography, and cardiac catheterization. Individuals were grouped by AI-enabled ECG probability of contemporaneous AF, taken as an indicator of underlying LA myopathy.

Results

Structural heart disease was more severe in patients with higher AI-probability of AF,

SUBMITTER: Verbrugge FH 

PROVIDER: S-EPMC8766932 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature