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A systematic review and meta-analysis, in the Heart, compared 21 available ECG algorithms across 22 studies, involving 3,483 patients (2,706 with RVOT and 777 with LVOT). The analysis assessed sensitivity, specificity, diagnostic odds ratios (DORs), and an overall superiority index.

Results revealed that the weighted hybrid score algorithm outperformed all others, showing the highest diagnostic accuracy with a superiority index of 21.2 and a DOR of 275.8. Its pooled sensitivity was 0.83, and its specificity was 0.92. It suggests that it may be the most reliable tool for differentiating LVOT from RVOT arrhythmias. The Earliest onset or peak/nadir in lead V2 algorithm demonstrated the lowest diagnostic performance.
 

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Key highlights
  • Differentiating LVOT from RVOT arrhythmias is crucial for ablation planning and treatment success.
  • A network meta-analysis of 22 studies and 3,483 patients compared 21 ECG algorithms for diagnostic accuracy.
  • The weighted hybrid score algorithm showed the highest accuracy, with strong sensitivity (0.83) and specificity (0.92).
  • The earliest onset or peak/nadir in the lead V2 algorithm performed the worst among those evaluated.
Source

He Z, Liu M, Ying P, Song M, Tan X. Diagnostic accuracy of electrocardiogram algorithms for differentiating left from right outflow tract ventricular arrhythmia: a systematic review and network meta-analysis. Heart. Published online July 3, 2025. Doi: http://doi.org/10.1136/heartjnl-2025-325916 

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A systematic review and meta-analysis have identified the weighted hybrid score as the most reliable ECG algorithm to distinguish between left (LVOT) and right (RVOT) ventricular outflow tract arrhythmias (OTVAs)  arrhythmias before ablation.

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