Diagnostic accuracy of electrocardiogram algorithms for differentiating left from right outflow tract ventricular arrhythmia: a systematic review and network meta-analysis.

Abstract

Accurate pre-ablation differentiation between left (LVOT) and right (RVOT) ventricular outflow tract arrhythmias (OTVAs) using ECG algorithms is essential for decision on vascular access and treatment strategy. However, the most reliable ECG algorithm remains unclear. We conducted a systematic review and network meta-analysis (NMA) to compare the diagnostic accuracy of available algorithms. We searched MEDLINE, EMBASE and Cochrane databases through 7 May 2025 for studies evaluating ECG algorithms against ablation-confirmed OTVA origin. A Bayesian diagnostic test accuracy NMA was performed to estimate pooled sensitivity, specificity, diagnostic odds ratios (DORs) and a superiority index (S) for each algorithm. Study quality was assessed using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool. From 620 records, 22 studies (3483 patients; 2706 RVOT, 777 LVOT) evaluating 21 ECG algorithms were included. The 'Weighted hybrid score' algorithm showed the highest diagnostic accuracy (S=21.2 (0.3, 39.0); DOR=275.8 (7.1, 1642.5)), with pooled sensitivity of 0.83 (0.53, 0.98) and specificity of 0.92 (0.68, 0.99). Conversely, the 'Earliest onset or peak/nadir in lead V2' algorithm had the lowest accuracy. Among existing ECG algorithms, the 'Weighted hybrid score' demonstrates superior diagnostic performance for differentiating LVOT from RVOT arrhythmias and is recommended for clinical application. CRD42024567531.