Optimizing Single-Lead Electrocardiogram Orientation Improves Detection of Left Ventricular Dysfunction

Single-lead electrocardiograms (ECGs) contain subtle markers of left ventricular (LV) dysfunction. We hypothesized that a synthesized frontal-plane vector would improve single-lead detection of reduced LV ejection fraction (LVEF) compared with standard limb leads.

This diagnostic study used paired 12-lead ECGs (10 s, 500 Hz) and echocardiograms obtained within 30 days from three Japanese hospital cohorts (one development and two external validation cohorts). For each beat, a derived lead, X, was synthesized from limb leads I and II as X(θ) = cosθ · I + sinθ · II, with θ scanned from 0° to 360°. A deep neural network generated beat-level predictions aggregated per recording to detect LVEF <50%. AUROC was the primary metric; accuracy, F1 score, sensitivity, and specificity were secondary metrics. Two performance peaks emerged near 30° and 210° (AUROC ≈0.857). Across repeated modeling from 180° to 270°, the 210° lead consistently ranked among the best single-lead models, matching or slightly exceeding aVR, although the 12-lead model remained superior. In external cohorts, the 210° lead achieved mean (±SD) AUROC 0.863±0.031, comparable to 12-lead and aVR (0.872±0.024 and 0.852±0.032; P>0.05).

An aVR-adjacent frontal vector near 210° enables single-lead detection of LV dysfunction that approaches 12-lead performance and exceeds other individual leads. Requiring only standard limb electrodes, this strategy could facilitate screening; further validation and mechanistic studies are warranted.