Predicting diabetic cardiomyopathy in type 2 diabetes: development and validation of a nomogram based on clinical and echocardiographic parameters

作者：Zilang Luo, Damao Pi, Tianlan Xi, Wenli Jiang, Feng Qiu, Jiadan Yang · 发表于：Frontiers in Endocrinology · 年份：2025 · DOI：10.3389/fendo.2025.1641114 · 被引用次数：1 · 研究领域：Cardiovascular Function and Risk Factors、Cardiac Imaging and Diagnostics、Cardiac Structural Anomalies and Repair

Objective Diabetic cardiomyopathy (DCM) is a myocardial dysfunction disorder driven by diabetes-associated metabolic disorders, significantly elevating the risk of heart failure in patients with type 2 diabetes mellitus (T2DM). We aimed to develop and validate a nomogram for individualized DCM risk prediction in T2DM populations. Methods This retrospective study enrolled 525 consecutive T2DM patients admitted to our hospital (June 2022-June 2024). Participants were randomly allocated to training (70%) or validation (30%) cohorts. Baseline clinical characteristics, laboratory profiles, and echocardiographic parameters were collected. Predictors were identified via univariate then multivariate logistic regression, followed by nomogram construction. Model validation included: (1) internal validation via 1000 bootstrap resamples; (2) discrimination assessed by the area under the receiver operating characteristic curve (AUC-ROC); (3) calibration evaluated using calibration plots and the Hosmer-Lemeshow goodness-of-fit test; (4) clinical utility determined by decision curve analysis (DCA) and clinical impact curves (CIC). Results Six independent predictors—age, duration of type 2 diabetes mellitus (T2DM Duration), systolic blood pressure (SBP), urinary albumin-to-creatinine ratio (UACR), left atrial diameter (LAD), and left ventricular posterior wall thickness at end-diastole (LVPWd)—were incorporated. The model showed excellent discrimination: AUC 0.947 (95% CI: 0.916-0.967) in tr...