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

Autor: Groepenhoff, F, Eikendal, ALM, Onland-Moret, NC, Bots, SH, Menken, R, Tulevski, II, Somsen, AG, Hofstra, L, den, Ruijter HM, Afd Pharmacoepi & Clinical Pharmacology
Přispěvatelé: Afd Pharmacoepi & Clinical Pharmacology, Cardiology, ACS - Atherosclerosis & ischemic syndromes
Rok vydání: 2020
Předmět:
Zdroj: Groepenhoff, F, Eikendal, A L M, Charlotte Onland-Moret, N, Bots, S H, Menken, R, Tulevski, I I, Somsen, A G, Hofstra, L & Den Ruijter, H M 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, e035928 . https://doi.org/10.1136/bmjopen-2019-035928
BMJ Open
BMJ Open, 10(4). BMJ Publishing Group Ltd
BMJ Open, 10(4):e035928. BMJ Publishing Group
ISSN: 2044-6055
DOI: 10.1136/bmjopen-2019-035928
Popis: 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.
Databáze: OpenAIRE