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Updated: May 16, 2025

Modeling and Evaluation of Murine Diabetic Cardiomyopathy Model
Published on: November 29, 2024
Development and validation of the CARE-DM model to predict the cardiovascular risk in older persons with type 2
Valerie Aponte Ribero1,2, Orestis Efthimiou1, Heba Alwan1
1Institute of Primary Health Care (BIHAM), University of Bern, Mittelstrasse 43, Bern 3012, Switzerland.
Aims:
No cardiovascular risk prediction model dedicated to individuals aged ≥70 years with diabetes is currently recommended by the European Society of Cardiology. We aimed to develop a new model, CArdiovascular Risk Estimation-Diabetes Mellitus (CARE-DM), to predict the risk of cardiovascular disease (CVD) in older adults with type 2 diabetes.
Methods And Results:
We developed a model to predict the risk of incident CVD in participants aged ≥65 years with diabetes using data from four population-based prospective cohorts, accounting for the competing risk of non-cardiovascular death. Pre-specified predictors were age, gender, smoking status, alcohol consumption, body mass index, total and HDL cholesterol, use of antihypertensive, cholesterol-lowering and glucose-lowering medication, diabetes duration, and glycated haemoglobin. We assessed model performance using measures of calibration and discrimination. We used a 10-fold cross-validation and a bootstrapping approach to correct estimates for optimism and conducted an internal-external cross-validation. A total of 6943 participants (median age 72 years, 56% women) with diabetes were included in the model development. Over a median follow-up of 6.3 (interquartile range 3.7, 7.2) years, 1204 (17.3%) participants experienced a CVD event. Internal validation with optimism correction showed adequate model performance with a C-index of 0.65 (95% confidence interval 0.63-0.67), an observed-to-expected ratio of 1.01 (0.95-1.08), and a calibration slope of 1.13 (0.95-1.31) at 5 years.
Conclusion:
The new CARE-DM model allows prediction of the incident CVD risk in older adults with type 2 diabetes. Independent external validation should be conducted to confirm the model's performance before implementation in clinical practice.
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