ReviewCJC open2023
Diagnostic Accuracy of ECG to Detect Left Ventricular Hypertrophy in Patients with Left Bundle Branch Block: A Systematic Review and Meta-analysis.
Review in CJC open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Electrical risk score and electrocardiographic markers in acute cholecystitis: a prospective cross-sectional study using explainable machine learning.BMC cardiovascular disorders · 2026Article
- Electrical risk score as a predictor of acute ischemic stroke and 30-day mortality: a prospective observational study.BMC neurology · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 11 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Electrocardiographic (ECG) criteria to detect left ventricular hypertrophy (LVH) in patients with left bundle branch block (LBBB) remain under debate. We conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy of different ECG criteria for diagnosing LVH in patients with LBBB. Methods: We searched PubMed, Embase, Cochrane, and LILACS for articles evaluating the diagnostic accuracy of ECG criteria for LVH in patients with LBBB published between 1984 and 2023. Echocardiogram, magnetic resonance imaging, or autopsy were used as the reference standard for diagnosis of LVH. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The co-primary outcomes were sensitivity, specificity, the diagnostic odds ratio, and likelihood ratios, estimated using a bivariate generalized linear mixed model for each ECG criterion. The prespecified protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO). Results: We included 12 studies with a total of 1023 patients. We analyzed 10 criteria for LVH on ECG, including the Sokolow-Lyon criterion, the Cornell criterion, the RaVL (R wave in aVL) criterion, the Gubner-Ungerleider criterion, and the Dálfo criterion, among others. The Dalfó criterion was used for 487 patients and had the highest pooled sensitivity of 86% (95% confidence interval [CI] 57%-97%). All the other criteria had poor sensitivities. The Gubner-Ungerleider criterion and the RV5 or RV6 > 25 mm criterion had the highest specificities, with the former being used for 805 patients, obtaining a specificity of 99% (95% CI 80%-100%) and the latter being used for 355 patients, obtaining a specificity of 99% (95% CI 94%-100%). Conclusions: In patients with LBBB, the use of ECG criteria had poor performance for ruling out LVH, mostly due to low sensitivities. None of the criteria analyzed demonstrated a balanced tradeoff between sensitivity and specificity, suggesting that ECG should not be used routinely to screen for LVH.
Identifiers
What OpenQuestion holds
Registered trials
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.