Key result
AI-enabled ECG score detects left atrial myopathy in HFpEF but fails to independently predict incident AF.
Why the study?
LA myopathy is common in HFpEF and leads to AF, but whether LA remodeling, dysfunction, altered hemodynamics, and incident AF risk could be identified from a single 12-lead ECG using AI was unknown.
Does an AI-enabled 12-lead ECG analysis identify left atrial myopathy and risk for incident atrial fibrillation in patients with heart failure and preserved ejection fraction?
Cohort (n=613)
Does an AI-enabled 12-lead ECG analysis identify left atrial myopathy and risk for incident atrial fibrillation in patients with heart failure and preserved ejection fraction?
A novel AI-enabled 12-lead ECG score can identify underlying left atrial myopathy in patients with HFpEF, though its independent predictive value for incident AF was attenuated after baseline adjustments.
Answers are grounded in this paper and cite their sources.
May identify left atrial myopathy in HFpEF but should not yet change practice; leaves open independent AF prediction after adjustment.
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. CONCLUSIONS: A novel AI-enabled score derived from a single 12-lead ECG identifies the presence of underlying LA myopathy in patients with heart failure and preserved ejection fraction as evidenced by structural, functional, and hemodynamic abnormalities, as well as long-term risk for incident AF. Further research is required to determine the role of the AI-enabled ECG in the evaluation and care of patients with heart failure and preserved ejection fraction.
No takes yet. Share an insight, caveat, or question.
Verbrugge et al. (2021) conducted a cohort in Heart failure and preserved ejection fraction (n=613). AI-enabled ECG analysis was evaluated on Incident atrial fibrillation (p=<0.001). An AI-enabled 12-lead ECG score identified underlying left atrial myopathy and long-term risk for incident AF in patients with HFpEF, though the AF risk association lost significance after adjustment.
Synapse has enriched 10 related papers. Consider them for comparative context: