Hemoglobin A1c risk score for the prediction of coronary artery disease in subjects with angiographically diagnosed coronary atherosclerosis

Abstract

Objective: To develop a risk score by incorporating Hemoglobin A1c(HbA1c) with traditional risk factors for the prediction of coronary artery disease (CAD) in Chinese subjects. Methods: A total of 196 consecutive subjects (131 males and 65 females) aged 38-89 years who underwent coronary angiography were enrolled in this study. HbA1c risk score sheets for the prediction of CAD were developed using age, gender and HbA1c. A receiver-operating characteristic curve analysis was used to determine the optimum cut-off levels of the HbA1c risk score for predicting CAD. Results: In the ROC curve analysis, the optimal cut-off value of the HbA1c score for predicting CAD was 5.1, with a sensitivity of 72.0% and a specificity of 75.5% (area under the curve 0.781, 95% confidence interval 0.709 to 0.854, p=0.000). Conclusions: The HbA1c score system is a simple and feasible method that can be used for the prediction of CAD. Large-scale studies are needed to further substantiate these results.