Key result
QRS notching marks PVC-triggered VF, with an ML algorithm differentiating cases with ~0.85 AUC.
Why the study?
PVCs are commonly seen but their association with malignant ventricular arrhythmias including VF and related ECG characteristics remain incompletely characterized.
Do specific ECG characteristics and a machine-learning algorithm distinguish patients with PVC-triggered VF from those with PVCs without VF?
Case-Control (n=82)
Yes
Do specific ECG characteristics and a machine-learning algorithm distinguish patients with PVC-triggered VF from those with PVCs without VF?
Answers are grounded in this paper and cite their sources.
Early repolarization and QRS notching are more prevalent in patients with PVC-triggered VF, and a machine-learning ECG algorithm can effectively distinguish these patients from those with benign PVCs.
Background: Although premature ventricular contractions (PVCs) are commonly seen, in some patients, PVCs are associated with malignant ventricular arrhythmias including ventricular fibrillation (VF). Objective: This study aimed to assess electrocardiographic (ECG) characteristics and apply a machine-learning (ML) algorithm in patients with PVC-triggered VF. Methods: We analyzed data from an international cohort of 82 patients undergoing ablation for PVCs (41 with PVC-triggered VF and 41 controls). We evaluated the prevalence of ECG characteristics in patients with PVC-triggered VF, including (1) early repolarization (ER) in inferior/lateral leads and (2) QRS notching of the sinus beat or PVC, and also applied an ML algorithm to assess the differences in the 2 patient cohorts. Results: In 41 patients with PVC-triggered VF, there was a median of 8 implantable cardioverter-defibrillator shocks per patient before PVC ablation. The mean coupling interval of the PVC to the antecedent sinus beat was 313 ± 130 ms. Compared with controls, ER (39% vs 17%) and QRS notching (71% vs 24%) were significantly more prevalent in the PVC-triggered VF group. After a median of 1 ablation (interquartile range 1-3), 82% of patients remained free of ventricular tachycardia/VF and implantable cardioverter-defibrillator shocks over a median follow-up of 400 days (90-2490). The ML ECG algorithm demonstrated reasonable discrimination between the 2 groups (area under the receiver-operating characteristic curve 0.85 [0.56-1.0]). Anterior ST-segment deviation and left bundle branch-like delay were salient contributors to ML prediction. Conclusion: In patients with PVC-triggered VF, ER and QRS notching were more prevalent than in patients with PVC without VF. An ML-based ECG algorithm effectively distinguished between the 2 groups.
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Maan et al. (2026) conducted a case-control in Premature ventricular contractions (PVCs) and PVC-triggered ventricular fibrillation (VF) (n=82). PVC-triggered VF vs. PVCs without VF was evaluated on QRS notching. Patients with PVC-triggered VF had a higher prevalence of QRS notching (71% vs 24%) than controls, and an ML-based ECG algorithm effectively distinguished the groups (AUC 0.85, CI 0.56-1.0).
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