Researchers have developed and validated a highly accurate nomogram that can predict an individual's risk of developing diabetic cardiomyopathy (DCM). This heart muscle disorder significantly raises risk of heart failure in patients with type 2 diabetes mellitus (T2DM). The analysis was published in the Frontiers in Endocrinology.

The retrospective study analyzed 525 T2DM patients admitted between June 2022 and June 2024. Using detailed clinical, laboratory, and echocardiographic data, the team identified six independent predictors of DCM, i.e., age, diabetes 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).

These predictors were integrated into a nomogram, which showed excellent performance. The model attained an area under the receiver operating characteristic curve (AUC) of 0.947 in the training group and 0.922 in the validation group.

Calibration analysis showed close agreement between predicted and actual outcomes, while decision curve analysis and clinical impact curves confirmed the model's real-world utility.