Key result
Stepwise 12-lead ECG algorithm correctly classifies RVOT versus LVOT arrhythmia origin in ~99% of patients.
Why the study?
Existing 12-lead ECG criteria show variable performance and often fail to differentiate RVOT from LVOT origin when the precordial transition during sinus rhythm and ventricular ectopy is identical.
Does a stepwise ECG algorithm accurately discriminate RVOT from LVOT origin in patients with idiopathic outflow tract ventricular arrhythmias?
Observational (n=133)
No
Does a stepwise ECG algorithm accurately discriminate RVOT from LVOT origin in patients with idiopathic outflow tract ventricular arrhythmias?
A novel 4-step ECG algorithm provides high accuracy (97%) in differentiating RVOT from LVOT origin in idiopathic outflow tract ventricular arrhythmias, including challenging cases with identical precordial transitions.
May aid ECG localization in ambiguous outflow tract cases; leaves open prospective validation before clinical adoption.
BACKGROUND: Accurate pre-procedural differentiation of right (RVOT) versus left ventricular outflow tract (LVOT) origin in idiopathic outflow tract ventricular arrhythmias may facilitate procedural planning and mapping strategy. However, existing 12-lead ECG criteria show variable performance and often fail to provide clear discrimination when the precordial transition during sinus rhythm and ventricular ectopy is identical. OBJECTIVE: To develop and evaluate a pragmatic, stepwise 12-lead ECG algorithm integrating amplitude- and duration-based parameters to discriminate RVOT from LVOT origin, with specific focus on identical precordial transitional patterns. METHODS: In this single-center retrospective study, consecutive patients undergoing successful catheter ablation for idiopathic outflow tract ventricular arrhythmias were included. The reference standard was the documented site of successful ablation (RVOT vs. LVOT). A stepwise ECG algorithm was developed, incorporating morphology-based criteria followed by a binary logistic regression model in patients with identical precordial transition. Diagnostic performance was assessed relative to the ablation site, and the regression model was internally validated using bootstrap resampling. RESULTS: A total of 133 patients were included (RVOT n = 76; LVOT n = 57). The 4-step algorithm correctly classified 131 of 133 patients (98.5%). In the subgroup with identical transitions during sinus rhythm and PVCs (n = 48), Step 4 demonstrated complete apparent classification, with an optimism-corrected accuracy of 96.1% and an AUC of 0.958 after bootstrap validation. The estimated optimism-corrected overall algorithm accuracy was 97%. CONCLUSION: A probability-based, stepwise ECG algorithm enables accurate discrimination between RVOT and LVOT origin, particularly in diagnostically challenging transitional patterns. If confirmed in external cohorts, this structured approach may support pre-procedural localization and hypothesis-driven mapping strategies in patients with idiopathic outflow tract ventricular arrhythmias.
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Krackhardt et al. (2026) conducted an observational in Idiopathic outflow tract ventricular arrhythmias (n=133). Stepwise 12-lead ECG algorithm vs. Documented site of successful ablation was evaluated on Correct classification of RVOT vs. LVOT origin. A stepwise 12-lead ECG algorithm correctly classified the origin of idiopathic outflow tract ventricular arrhythmias in 98.5% of patients.
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