Weighted hybrid score predicts outflow tract ventricular arrhythmia origin in patients with intraventricular conduction disorders or paced rhythm: an international multicenter study
摘要
Accurate identification of the site of origin (SOO) of outflow tract ventricular arrhythmias (OTVAs) is critical for effective ablation planning. Accuracy of the existing algorithms/scores in patients with wide baseline QRS has not been previously described. This study sought to evaluate the performance of available algorithms/scores in predicting the OTVA-SOO in patients with wide baseline QRS due to intraventricular conduction abnormalities or paced rhythm (NCT06602635).
MethodsEighty-eight patients with intraventricular conduction disturbances (baseline QRS >110 ms) or a paced rhythm who underwent OTVA ablation in 9 European centers were included. The predictive performance of the existing algorithms/scores was compared using receiver operating characteristic curve analysis, accuracy, sensitivity, and specificity.
ResultsMedian baseline QRS duration was 122ms (114–144), sixty-five (73.9%) patients had OTVA originating from left ventricular outflow tract (LVOT) and 23 (26.1%) from right ventricular outflow tract. LVOT-SOO patients were older (69 vs. 56 years, p = 0.01), more frequently hypertensive (55.4% vs. 26.1%, p = 0.03), cardiac implantable electronic device (CIED)-carriers (33.8% vs. 4.3%, p = 0.01), and had lower LV ejection fraction (45% vs. 56%, p = 0.05). LVOT-OTVAs more often showed early R/S precordial transition (63.1% vs. 0.0%, p < 0.001). The Weighted Hybrid Score (WHS), which incorporates clinical and ECG variables, achieved the highest diagnostic performance (AUC 0.971), surpassing ECG-based scores (AUC from 0.919 to 0.510). A WHS ≥ 2 accurately predicted a LVOT-SOO in 80 of 88 cases (accuracy 91.0%), with 92% sensitivity and 91% specificity, outperforming existing scores (accuracy from 59% to 83%).
ConclusionsIn patients with a wide baseline QRS the most frequent OTVA-SOO is the LVOT. The WHS demonstrated accurate prediction of the OTVA-SOO in this specific population, outperforming previously published ECG-based algorithms/scores.
Graphical Abstract