Dilated cardiomyopathy (DCM) is a common and serious heart disease characterized by left ventricular enlargement and impaired pumping function, with adverse prognosis (including heart failure, arrhythmia, heart-related hospitalization, and death) being a major concern for patients. Currently, a critical gap exists in accurately predicting which DCM patients are at high risk of these severe outcomes, limiting targeted clinical care. This observational, non-invasive study aims to develop and validate a clinical prediction model for early risk warning of adverse prognosis in DCM patients. The model integrates multi-parameter stress perfusion cardiac magnetic resonance (MP stress perfusion CMR)-a safe, high-resolution imaging technique that assesses cardiac structure, function, blood perfusion, and tissue damage under mild stress-and standard clinical data (e.g., age, gender, blood pressure, and routine heart test results). The model will be trained and tested using follow-up data from hundreds of DCM patients, with the analysis identifying patterns in CMR and clinical data associated with adverse outcomes. Once validated for accuracy, the model will provide doctors with personalized risk scores to prioritize care for high-risk patients (e.g., early intervention, close monitoring) and avoid over-treatment for lower-risk individuals. Beyond clinical application, the study will enhance understanding of DCM progression, laying the groundwork for improved diagnostic tools, more effective treatments, and better strategies to prevent DCM-related complications, ultimately improving patient quality of life and reducing mortality.
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SCD-related events
Timeframe: 1 year, 3 years, and 5 years after CMR examination