Evidence map›Paper›PMID 37487685›Full record

SynthesisBMJ open2023

Diagnostic accuracy of different ECG-based algorithms in wide QRS complex tachycardia: a systematic review and meta-analysis.

Xingxing Sun, Yanling Teng, Shengnan Mu, Yilian Wang, Hongwu Chen

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xingxing Sun *Department of Cardiology, The Second People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, China.ORCID 0000-0002-7283-0981
Yanling Teng *Department of Cardiology, The First people's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, China.
Shengnan MuDepartment of Cardiology, The Second People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, China.
Yilian WangDepartment of Cardiology, The Second People's Hospital of Lianyungang, Affiliated to Kangda College of Nanjing Medical University, Lianyungang, China chw2003_0_79@163.com 497857934@qq.com.ORCID 0000-0002-7283-0981
Hongwu ChenDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China chw2003_0_79@163.com 497857934@qq.com.ORCID 0000-0002-0006-2485

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSeveral 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.

designSystematic 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

resultsIn 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.

conclusionsECG-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.

Indexed as

ElectrocardiographyTachycardiaAlgorithmsArrhythmias, CardiacDiagnosis, DifferentialHumansSensitivity and Specificityaccident & emergency medicinecardiologypacing & electrophysiology

Identifiers

PMID37487685
PMCPMC10373685

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.