Coronary artery disease prediction in women and men using chest pain characteristics and risk factors: an observational study in outpatient clinics

Publication date

2020-04

Authors

Groepenhoff, F
Eikendal, ALM
Onland-Moret, NC
Bots, Sophie H.ORCID 0000-0002-4483-5582ISNI 0000000506342455
Menken, R
Tulevski, II
Somsen, AG
Hofstra, L
den, Ruijter HM

Editors

Advisors

Supervisors

Document Type

Article
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License

cc_by_nc

Abstract

Objectives To 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 setting This is an observational study performed at outpatient cardiology centres of the Netherlands. Participants The study population consisted of 1028 patients with non-acute chest pain (505 women). Analysis and results Twenty-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). Conclusions In 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.

Keywords

SDG 3 - Good Health and Well-being

Citation

Groepenhoff, F, Eikendal, ALM, Onland-Moret, NC, Bots, SH, Menken, R, Tulevski, II, Somsen, AG, Hofstra, L & den, R HM 2020, 'Coronary artery disease prediction in women and men using chest pain characteristics and risk factors: an observational study in outpatient clinics', BMJ Open, vol. 10, no. 4. https://doi.org/10.1136/bmjopen-2019-035928