To quantify the risk factors for aspirin resistance so as to increase the prognosis for risk of coronary heart disease, and to establish a predictive model for aspirin resistance in order to guide the clinical anti-platelet therapy.

A total of 938 elderly male patients with stable coronary heart disease (CHD) receiving oral aspirin therapy (>75 mg/d) over 2 months were included in this study. Their clinical data were collected. Logistic regression analysis was performed to establish a predictive model and risk score for aspirin resistance. Hosmer Lemeshow (H-L) test and an area under the receiver operating characteristic (ROC) curve (the area under the ROC curve) were performed to test the calibration and discrimination of the model.

Seven risk factors were included in the predictive model, including serum creatinine (>110 μmol/L: score of 1), fasting blood glucose (>7.0 mmol/L: score of 1), hyperlipidemia (score of 1), number of coronary arteries in lesion (2 branches: score of 2, ≥3 branches: score of 4), body mass index〔(20-25) kg/m²: score of 2, >25 kg/m²: score of 4〕, percutaneous coronary intervention (score of 2), smoking (score of 3). H-L test showed P≥0.05 and the area under the ROC curve>0.70 in this model.

the risk factors for aspirin resistance, and establishing a valid predictive model for aspirin resistance, could provide an important reference for anti-platelet therapy in CHD patients.

Aspirin; Coronary disease; Proportional hazards models