Abstract
PURPOSE: Cardiovascular disease is the leading cause of mortality in patients with type 2 diabetes mellitus (T2DM). This study aimed to develop and validate a nomogram for predicting the risk factors for coronary heart disease (CHD) in T2DM in the population of northwestern China. PATIENTS AND METHODS: The records of 2357 T2DM patients who were treated in the First Affiliated Hospital of Xinjiang Medical University from July 2021 to July 2022 were reviewed. After some data (n =239) were excluded, 2118 participants were included in the study and randomly divided into a training set (n =1483) and a validation set (n = 635) at a ratio of 3:1. Univariate and stepwise regression analysis was performed to screen risk factors and develop predictive models. The results of logistic regression are presented through a nomogram. The C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were employed to verify the distinction, calibration, and clinical practicality of the model. RESULTS: The stepwise logistic regression analysis suggested that independent factors in patients with T2DM combined with CHD were age, gender, hypertension (HTN), glycated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and Uygur, which were associated with the occurrence of CHD. The nomogram demonstrated good discrimination with a C-index of 0.771 (95% CI, 0.741, 0.800) in the training set and 0.785 (95% CI, 0.743, 0.828) in the validation set. The area under curve (AUC) of the ROC curves were 0.771 (95% CI, 0.741, 0.800) and 0.785 (95% CI, 0.743, 0.828) in the training and validation sets, respectively. The nomogram was well-calibrated. The DCA revealed that the nomogram was clinically valuable. CONCLUSION: A nomogram based on 7 clinical characteristics was developed to predict CHD in patients with T2DM.