Observational studyBMJ open2020
Coronary artery disease prediction in women and men using chest pain characteristics and risk factors: an observational study in outpatient clinics.
Observational study in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
- Real-world risk stratification for coronary heart disease: a one-year prediction model using health information exchange data.BMC public health · 2025Article
- Sex matters: the frequently overlooked importance of considering sex in computational models.Frontiers in physiology · 2023Review
- Addressing persistent evidence gaps in cardiovascular sex differences research - the potential of clinical care data.Frontiers in global women's health · 2022Article
- Routine clinical care data from thirteen cardiac outpatient clinics: design of the Cardiology Centers of the Netherlands (CCN) database.BMC cardiovascular disorders · 2021Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo assess the diagnostic value of non-acute chest pain characteristics for coronary artery disease in women and men referred to outpatient cardiology clinics. DESIGN AND
settingThis is an observational study performed at outpatient cardiology centres of the Netherlands.
participantsThe study population consisted of 1028 patients with non-acute chest pain (505 women). ANALYSIS AND
resultsTwenty-four women (5%) and 75 men (15%) were diagnosed with coronary artery disease by invasive coronary angiography or CT angiography during regular care follow-up. Elastic net regression was performed to assess which chest pain characteristics and risk factors were of diagnostic value. The overall model selected age, provocation by temperature or stress, relief at rest and functional class as determinants and was accurate in both sexes (area under the curve (AUC) of 0.76 (95% CI 0.68 to 0.85) in women and 0.83 (95% CI 0.78 to 0.88) in men). Both sex-specific models selected age, pressuring nature, radiation, duration, frequency, progress, provocation and relief at rest as determinants. The female model additionally selected dyspnoea, body mass index, hypertension and smoking while the male model additionally selected functional class and diabetes. The sex-specific models performed better than the overall model, but more so in women (AUC: 0.89, 95% CI 0.81 to 0.96) than in men (AUC: 0.84, 95% CI 0.73 to 0.90).
conclusionsIn both sexes, the diagnostic value of non-acute chest pain characteristics and risk factors for coronary artery disease was high. Provocation, relief at rest and functional class of chest pain were the most powerful diagnostic predictors in both women and men. When stratified by sex the performance of the model improved, mostly in women.
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