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Updated: Oct 24, 2025

Modeling and Evaluation of Murine Diabetic Cardiomyopathy Model
Published on: November 29, 2024
Novel biomarkers for subtle myocardial involvement in type I diabetes mellitus
Sonia A El-Saiedi1, Mona H Hafez1, Yasser M Sedky1
1Division of Pediatric Cardiology, Pediatrics Unit.
Insights
Plasma cardiotrophin (CT-1) best predicts left ventricular systolic dysfunction, while brain natriuretic peptide (BNP) excels in predicting diastolic dysfunction in children with type 1 diabetes mellitus.
Area of Science:
- Pediatric Cardiology
- Diabetology
- Biomarker Research
Background:
- Type 1 diabetes mellitus (T1DM) can lead to impaired cardiac function in children.
- Identifying reliable biomarkers is crucial for early detection of diabetic cardiomyopathy.
Purpose of the Study:
- To identify the optimal cardiac biomarker for predicting left ventricular (LV) and right ventricular (RV) dysfunction in pediatric T1DM.
- To compare the efficacy of various biomarkers including CT-1, IGFBP-7, and BNP.
Main Methods:
- A case-control study involving 55 children with T1DM and 55 healthy controls.
- Echocardiography (including 3D-STE and TDI) assessed LV and RV systolic/diastolic functions.
- Measurements included HbA1c, troponin I, BNP, CT-1, activin-A, TGF-β, and IGFBP-7.
Main Results:
- Children with T1DM exhibited RV and LV systo-diastolic dysfunction compared to controls.
- CT-1 was the best predictor of LV systolic dysfunction (sensitivity 69%).
- IGFBP-7 best predicted RV systolic dysfunction (sensitivity 63%), while BNP was optimal for diastolic dysfunction (sensitivity 82% for both RV and LV).
Conclusions:
- CT-1 demonstrates diagnostic superiority for LV systolic dysfunction in pediatric T1DM.
- BNP remains a key marker for diastolic dysfunction and heart failure with preserved ejection fraction (HFpEF).
- BNP's accuracy and availability support its use as a screening tool for diabetic patients.
Background:
Evaluation of certain biomarkers could be used to predict left ventricular (LV) and right ventricular (RV) function impairment in children with type 1 diabetes mellitus. The aim of this study was to determine the best cardiac biomarker for prediction of diabetic cardiomyopathy.
Methodology:
This study was designed as case-control study. A total of 55 children with type 1 diabetes mellitus (group/G1) and 55 healthy controls (G2) were subjected to echocardiography including 3D-Speckle Tracking Echocardiography and tissue Doppler imaging for assessment of RV and LV systolic and diastolic functions. As well as HbA1c, troponin I, brain natriuretic peptide (BNP), plasma cardiotrophin (CT-1), activin-A, transforming growth factor-β, and human insulin-like growth factor binding protein-7 (IGFBP-7) measurements.
Results:
Diabetic patients showed RV and LV systo-diastolic dysfunction compared to controls, the best predictor of LV systolic dysfunction was CT-1 (sensitivity: 69%, while IGFBP-7 was found to be the best predictor of RV systolic dysfunction (sensitivity: 63%). BNP was found to the best predictor of diastolic RV and LV dysfunction (sensitivity: 82% for both).
Conclusion:
CT-1 has proven to be a diagnostic superiority in LV systolic dysfunction whilst BNP continues to prove every day through our study and through many others that it is the chief marker of diastolic dysfunction and HFpEF. This potential accuracy and the increasing availability of BNP in the outpatient setting make it clear that it should be used as a screening test for diabetic patients.
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