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Utility of ECG-Vision for Surveillance of Left Ventricular Dysfunction in Patients With Hypertrophic Cardiomyopathy

Aakash Bavishi1, John Fritzlen2, Marybeth Soutar3

  • 1University of Illinois-Chicago (A.B.).

Circulation. Heart Failure
|August 10, 2026
PubMed

Insights

Artificial intelligence (AI)-enabled ECGs show promise in predicting left ventricular systolic dysfunction (LVSD) in hypertrophic cardiomyopathy patients on mavacamten. This AI tool could reduce the need for frequent echocardiograms, improving access to care.

Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Obstructive hypertrophic cardiomyopathy (HCM) requires frequent monitoring for left ventricular systolic dysfunction (LVSD) using transthoracic echocardiograms (TTEs).
  • Current monitoring methods can be burdensome and limit access, particularly in rural or underserved areas.
  • Mavacamten is a myosin inhibitor used to treat obstructive HCM.

Purpose of the Study:

  • To evaluate the performance of an artificial intelligence (AI)-enabled ECG tool in predicting LVSD in patients with obstructive HCM treated with mavacamten.
  • To assess the potential of AI-ECG as an alternative or adjunctive tool to TTE for LVSD monitoring.

Main Methods:

  • A cohort of 147 patients with obstructive HCM initiated on mavacamten underwent paired ECG and TTE at baseline and follow-up.
  • A validated AI-enabled ECG algorithm was used to predict the probability of LVSD (defined as left ventricular ejection fraction <50%).
  • Sensitivity, specificity, positive predictive value, negative predictive value, and AUC were calculated, accounting for repeated measures.

Main Results:

  • The AI-enabled ECG demonstrated high sensitivity (100%) and negative predictive value (100%) for detecting LVSD at a 20% probability threshold.
  • The area under the curve (AUC) was 0.94, indicating strong predictive performance.
  • Patient-level classification concordance between AI-ECG and TTE was 86%.

Conclusions:

  • AI-enabled ECG tools show high sensitivity and NPV for detecting LVSD in obstructive HCM patients on mavacamten.
  • While estimates were imprecise due to infrequent LVSD events, findings support AI-ECG as a potential adjunctive triage tool.
  • Prospective, multicenter validation is recommended to confirm these exploratory findings.
Abstract

Keywords:
artificial intelligencecardiomyopathy, hypertrophicechocardiographyelectrocardiographyprobability

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