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Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis
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 intel...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373685/ https://www.ncbi.nlm.nih.gov/pubmed/37487685 http://dx.doi.org/10.1136/bmjopen-2022-069273 |
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author | Sun, Xingxing Teng, Yanling Mu, Shengnan Wang, Yilian Chen, Hongwu |
author_facet | Sun, Xingxing Teng, Yanling Mu, Shengnan Wang, Yilian Chen, Hongwu |
author_sort | Sun, Xingxing |
collection | PubMed |
description | 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: Two independent reviewers extracted data and assessed risk of bias. Data were pooled using random-effects model and expressed as mean differences with 95% CIs. Heterogeneity was calculated by the I(2) 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. |
format | Online Article Text |
id | pubmed-10373685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-103736852023-07-28 Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis Sun, Xingxing Teng, Yanling Mu, Shengnan Wang, Yilian Chen, Hongwu BMJ Open Cardiovascular Medicine 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: Two independent reviewers extracted data and assessed risk of bias. Data were pooled using random-effects model and expressed as mean differences with 95% CIs. Heterogeneity was calculated by the I(2) 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. BMJ Publishing Group 2023-07-24 /pmc/articles/PMC10373685/ /pubmed/37487685 http://dx.doi.org/10.1136/bmjopen-2022-069273 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Cardiovascular Medicine Sun, Xingxing Teng, Yanling Mu, Shengnan Wang, Yilian Chen, Hongwu Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis |
title | Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis |
title_full | Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis |
title_fullStr | Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis |
title_full_unstemmed | Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis |
title_short | Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis |
title_sort | diagnostic accuracy of different ecg-based algorithms in wide qrs complex tachycardia: a systematic review and meta-analysis |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373685/ https://www.ncbi.nlm.nih.gov/pubmed/37487685 http://dx.doi.org/10.1136/bmjopen-2022-069273 |
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