Key result
ECG-based algorithms for diagnosing wide QRS complex tachycardia demonstrated an overall sensitivity of 88.89% and specificity of 70.55%, with a diagnostic odds ratio of 19.17 (95% CI 11.45-32.10).
Why the study?
Several ECG-based algorithms have been proposed to distinguish wide QRS complex tachycardia, but a comprehensive comparison of their accuracy was lacking.
What is the diagnostic accuracy of various non-artificial intelligence ECG-based algorithms for wide QRS complex tachycardia?
Meta-Analysis (n=3,966)
What is the diagnostic accuracy of various non-artificial intelligence ECG-based algorithms for wide QRS complex tachycardia?
Odds Ratio: 19.17 (95% CI 11.45–32.1)
ECG-based algorithms exhibit high sensitivity and moderate specificity in diagnosing wide QRS complex tachycardia, suggesting that combining algorithms like Brugada or Vereckei-aVR with RWPT-II may optimize diagnostic accuracy.
Limited specificity advises against sole reliance on ECG algorithms; leaves open need for refinement and prospective validation.
OBJECTIVE: Several ECG-based algorithms have been proposed to enhance the effectiveness of distinguishing Wide QRS complex tachycardia (WCT), but a comprehensive comparison of their accuracy is still lacking. This meta-analysis aimed to assess the diagnostic precision of various non-artificial intelligence ECG-based algorithms for WCT. DESIGN: Systematic review with meta-analysis. DATA SOURCES: Electronic databases (PubMed, MEDLINE, the Cochrane Library, and Web of Science) are searched up to May 2022. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: All studies reporting the diagnostic accuracy of different ECG-based algorithms for WCT are included. The risk of bias in included studies is assessed using the Cochrane Collaboration's risk of bias tools. DATA EXTRACTION AND SYNTHESIS: method. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied to assess the internal validity of the diagnostic studies. RESULTS: In total, 467 studies were identified, and 14 studies comprising 3966 patients were included, involving four assessable ECG-based algorithms: the Brugada algorithm, Vereckei-pre algorithm, Vereckei-aVR algorithm and R wave peak time of lead II (RWPT-II) algorithm. The overall sensitivity was 88.89% (95% CI: 85.03 to 91.86), with a specificity of 70.55% (95% CI: 62.10 to 77.79) and a diagnostic OR (DOR) of 19.17 (95% CI: 11.45 to 32.10). Heterogeneity of the DOR was 89.1%. The summary sensitivity of each algorithm was Brugada 90.25%, Vereckei-pre 94.80%, Vereckei-aVR 90.35% and RWPT-II 78.15%; the summary specificity was Brugada 64.02%, Vereckei-pre 75.40%, Vereckei-aVR 60.88% and RWPT-II 88.30% and the summary DOR was Brugada 16.48, Vereckei-pre 60.70, Vereckei-aVR 14.57 and RWPT-II 27.00. CONCLUSIONS: ECG-based algorithms exhibit high sensitivity and moderate specificity in diagnosing WCT. A combination of Brugada or Vereckei-aVR algorithm with RWPT-II could be considered to diagnose WCT. PROSPERO REGISTRATION NUMBER: CRD42022344996.
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Sun et al. (2023) conducted a meta-analysis in Wide QRS complex tachycardia (n=3,966). ECG-based algorithms was evaluated on Diagnostic accuracy for wide QRS complex tachycardia (DOR 19.17, 95% CI 11.45-32.10). ECG-based algorithms for diagnosing wide QRS complex tachycardia demonstrated an overall sensitivity of 88.89% and specificity of 70.55%, with a diagnostic odds ratio of 19.17 (95% CI 11.45-32.10).
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