Author Identifier (ORCID)
Zhuoqiao He: https://orcid.org/0009-0000-5016-0684
Manshu Song: https://orcid.org/0000-0003-1433-7192
Abstract
Background: 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. Methods: 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. Results: 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. Conclusions: Among existing ECG algorithms, the Weighted hybrid score' demonstrates superior diagnostic performance for differentiating LVOT from RVOT arrhythmias and is recommended for clinical application. PROSPERO registration number: CRD42024567531.
Document Type
Journal Article
Date of Publication
1-1-2025
Publisher
BMJ Publishing Group
School
School of Medical and Health Sciences
RAS ID
83524
Funders
National Natural Science Foundation of China (82073659) / Funding for Guangdong Medical Leading Talent / First Affiliated Hospital of Shantou University Medical College, China (2019-2022) / Grant for Key Disciplinary Project of Clinical Medicine under the High-level University Development Program, Guangdong, China (2024-2025) / SUMC Scientific Research Initiation Grant (009-510858071) / Western Australian Future Health Research and Innovation Fund (WANMA/Ideas2023-24/10)
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
He, Z., Liu, M., Ying, P., Song, M., & Tan, X. (2025). Diagnostic accuracy of electrocardiogram algorithms for differentiating left from right outflow tract ventricular arrhythmia: A systematic review and network meta-analysis. Heart. Advance online publication. https://doi.org/10.1136/heartjnl-2025-325916