ArticleInternational journal of general medicine2026
A Nomogram Integrating Clinical and Cardiac Imaging for Predicting Short-Term Left Ventricular Ejection Fraction Decline in Patients with Duchenne Muscular Dystrophy.
Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: This study aimed to develop and validate a nomogram for predicting short-term LVEF decline in patients with DMD. Methods: This was a single-center retrospective cohort study enrolling male patients diagnosed with DMD at Sun Yat-sen Memorial Hospital, Sun Yat-sen University, between 2015 and 2025. Data collected included patient age, cardiac troponin I (cTnI) levels, history of steroid therapy, baseline echocardiographic LVEF, and CMR data (including LGE and native T1 values). The primary outcome was the decline in LVEF (ΔLVEF ≤ -10%) during follow-up within 12 months. Least absolute shrinkage and selection operator (LASSO) logistic regression analysis was employed to identify independent risk factors and construct a nomogram-based predictive model. Model performance was assessed by the area under the receiver operating characteristic (ROC) curve and internally validated using bootstrap resampling (1000 repetitions). Results: A total of 102 patients were included, of whom 38 (37.3%) exhibited a decline in LVEF. Multivariable analysis identified older age (OR 1.16, 95% CI 1.04-1.30, p = 0.009), abnormal cTnI (cTnI ≥ 0.04 ng/mL) (OR 7.27, 95% CI 1.46-36.28, p = 0.016), longer steroid duration (OR 1.72, 95% CI 1.09-2.71, p = 0.020, likely reflecting disease severity), the presence of LGE (OR 5.45, 95% CI 1.27-23.43, p = 0.023), and higher native T1 values (OR 1.02, 95% CI 1.01-1.04, p = 0.001) as independent risk factors. A higher baseline LVEF was protective (OR 0.81, 95% CI 0.72-0.91, p<0.001). The predictive model demonstrated excellent discrimination, with an AUC of 0.943 (95% CI 0.901-0.985). Internal validation yielded an optimism-corrected C-index of 0.922. Conclusion: This study successfully established a comprehensive prediction model incorporating clinical and imaging variables, which can accurately identify DMD patients at risk for short-term LVEF decline. The model demonstrated high discriminative ability (AUC 0.943) in this retrospective, single-center cohort; however, these results are preliminary and require external validation.
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