SynthesisFrontiers in cardiovascular medicine2022
Performance of Multiparametric Models in Patients With Brugada Syndrome: A Systematic Review and Meta-Analysis.
Synthesis in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Multiparametric models for predicting major arrhythmic events in Brugada syndrome: a systematic review and critical appraisal.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Pooled it
- Beyond the type 1 pattern: comprehensive risk stratification in Brugada syndrome.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2025Review
- Current perspectives on risk prediction and genetic basis of Brugada syndrome.Frontiers in cardiovascular medicine · 2025Review
- Brugada syndrome risk scores: what we've learned and what's next.Frontiers in cardiovascular medicine · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Multiparametric models have shown better risk stratification in Brugada syndrome. Recently, these models have been validated in different populations. Aims: To perform a systematic review and meta-analysis of the predictive performance of three validated multiparametric models (Delise model, Sieria model, and Shanghai score). Methods: We searched PubMed, Embase, MEDLINE, Web of Science, and Ovid for studies validating the risk multiparametric model. A Sieria score > 2 and Shanghai score ≥ 4 were considered to indicate higher risk. Performance estimates were summarized using a random-effects model. Results: Seven studies were included, with sample sizes of 111-1,613. The follow-up duration was 3.3-10.18 years. The Sieria model had a pooled area under the curve (AUC), sensitivity, and specificity of 0.71 [95% confidence interval (CI): 0.67-0.75], 57% (95% CI: 35-76), and 71% (95% CI: 62-79), respectively. The Shanghai score had an AUC of 0.63-0.71, 68.97-90.67% sensitivity, and 43.53-63.43% specificity. The AUC of the Delise model was 0.77-0.87; however, the optimal cut-off was not identified. Conclusions: The three models exhibited moderate discriminatory ability for Brugada syndrome. The Sieria model has poor sensitivity and moderate specificity, whereas the Shanghai score has poor specificity and moderate sensitivity.
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