Huang_2024_Front.Endocrinol.(Lausanne)_15_1416234

OBJECTIVE: To investigate the factors influencing accelerated aging in patients with type 2 diabetes mellitus (T2DM) and coronary heart disease (CHD). METHODS: A total of 216 patients diagnosed with T2DM and CHD between August 2019 and August 2023 at Xuzhou Central Hospital were selected. Patients were divided into an aging group and a non-aging group, based on the positive or negative values of phenotypic age acceleration (PhenoAgeAccel). Logistic regression analysis was conducted. Variables that had a univariate analysis P< 0.05 were included in the multivariate analysis to identify factors influencing aging in patients with T2DM and CHD, and the area under the curve of the model was reported. RESULTS: This study included 216 patients, with 89 in the accelerated aging group, and 127 in the non-accelerated aging group. The average age of patients was 70.40 (95% CI: 69.10-71.69) years, with 137 males (63.4%). Compared with the non-accelerated aging group, patients in the accelerated aging group were older, with a higher proportion of males, and a higher prevalence of hypertension, stable angina pectoris, and unstable angina pectoris. Multivariate Logistic regression analysis indicated that the absolute value of neutrophils (NEUT#), urea (UREA), adenosine deaminase (ADA), and the triglyceride-glucose index (TyG) were risk factors for accelerated aging, while cholinesterase (CHE) was a protective factor. For each unit increase in NEUT#, UREA, ADA, and TyG, the risk of aging increased by 64%, 48%, 10%, and 789%, respectively. The overall area under the receiver operating characteristic (ROC) curve of the model in the training set was 0.894, with a 95% confidence interval (CI) of 0.851-0.938. CONCLUSION: NEUT#, CHE, UREA, ADA, and TyG are predictors of accelerated aging in patients with T2DM and CHD, with the model showing favorable overall predictive performance.