SynthesisBMJ open2021
Discrimination capability of pretest probability of stable coronary artery disease: a systematic review and meta-analysis suggesting how to improve validation procedures.
Synthesis in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial.JMIR research protocols · 2025Article
- The effect of individual exercise rehabilitation program on ischemic burden and cardiac function in patients with ischemic non-obstructive coronary heart disease: a randomized parallel controlled clinical trial.Frontiers in cardiovascular medicine · 2025Article
- Serum BAFF level is associated with the presence and severity of coronary artery disease and acute myocardial infarction.BMC cardiovascular disorders · 2024Article
- Machine learning models using symptoms and clinical variables to predict coronary artery disease on coronary angiography.Postepy w kardiologii interwencyjnej = Advances in interventional cardiology · 2024Article
- Diagnostic and Therapeutic Strategies for Stable Coronary Artery Disease Following the ISCHEMIA Trial.JACC. Asia · 2023Review
- Monocyte-to-high-density lipoprotein ratio as a predictor for patients with Takayasu arteritis and coronary involvement: a double-center, observational study.Frontiers in immunology · 2023Observational
- Emerging biomarkers for the detection of cardiovascular diseases.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2022Review
- Risk vs. disease: the role of artificial intelligence in avoiding unneeded testing.European heart journal. Digital health · 2022Article
- Predictive Added Value of Selected Plasma Lipids to a Re-estimated Minimal Risk Tool.Frontiers in cardiovascular medicine · 2021Article
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Authors and funding
9 authors.
Funding
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Abstract
objectiveExternally validated pretest probability models for risk stratification of subjects with chest pain and suspected stable coronary artery disease (CAD), determined through invasive coronary angiography or coronary CT angiography, are analysed to characterise the best validation procedures in terms of discriminatory ability, predictive variables and method completeness.
designSystematic review and meta-analysis. DATA SOURCES: Global Health (Ovid), Healthstar (Ovid) and MEDLINE (Ovid) searched on 22 April 2020. ELIGIBILITY CRITERIA: We included studies validating pretest models for the first-line assessment of patients with chest pain and suspected stable CAD. Reasons for exclusion: acute coronary syndrome, unstable chest pain, a history of myocardial infarction or previous revascularisation; models referring to diagnostic procedures different from the usual practices of the first-line assessment; univariable models; lack of quantitative discrimination capability.
methodsEligibility screening and review were performed independently by all the authors. Disagreements were resolved by consensus among all the authors. The quality assessment of studies conforms to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A random effects meta-analysis of area under the receiver operating characteristic curve (AUC) values for each validated model was performed.
results27 studies were included for a total of 15 models. Besides age, sex and symptom typicality, other risk factors are smoking, hypertension, diabetes mellitus and dyslipidaemia. Only one model considers genetic profile. AUC values range from 0.51 to 0.81. Significant heterogeneity (p<0.003) was found in all but two cases (p>0.12). Values of I
conclusionsWe recommend a clearer statement of endpoints, their consistent measurement both in the derivation and validation phases, more comprehensive validation analyses and the enhancement of threshold validations to assess the effects of pretest models on clinical management. PROSPERO REGISTRATION NUMBER: CRD42019139388.
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