ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Cardiovascular Endocrinology
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1641114
This article is part of the Research TopicThe Complex Phenotype of Diabetic Cardiomyopathy: Clinical Indicators and Novel Treatment Targets – Volume IIView all 5 articles
Predicting Diabetic Cardiomyopathy in Type 2 Diabetes: Development and Validation of a Nomogram Based on Clinical and Echocardiographic Parameters
Provisionally accepted
- 1Department of Pharmacy, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- 2First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- 3Chongqing Medical University College of Pharmacy, Chongqing, China
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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.: 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 training and 0.922 (95% CI: 0.870-0.956) in validation cohorts. Calibration indicated strong agreement (Hosmer-Lemeshow χ² = 9.2119, P = 0.3247). DCA and CIC confirmed clinical utility. Conclusions: This nomogram integrates routine clinical/echocardiographic parameters to predict DCM risk in T2DM patients, facilitating individualized risk stratification and guiding early cardioprotective interventions in high-risk populations. Clinical trial registration: registration number: ChiCTR2400093755.
Keywords: Diabetic cardiomyopathy, type 2 diabetes mellitus, nomogram, Risk prediction model, Echocardiographic
Received: 04 Jun 2025; Accepted: 22 Jul 2025.
Copyright: © 2025 Luo, Pi, Xi, Jiang, Qiu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Feng Qiu, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
Jiadan Yang, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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