This retrospective multicenter cohort study aims to develop and validate an artificial intelligence model integrating electrocardiography (ECG) and chest radiography (CXR) to predict future progression of regurgitant valvular heart disease (rVHD), including aortic, mitral, and tricuspid regurgitation. Adult patients with ECG, CXR, and echocardiography obtained within 60 days, together with follow-up echocardiographic data, are included. The primary objective is to determine whether multimodal ECG+CXR modeling improves prediction of progression to moderate or severe regurgitation beyond ECG-only or CXR-only models. Secondary objectives include evaluation of clinical utility, risk stratification, and model interpretability. This study is intended to assess whether routinely acquired ECG and CXR can be used to support surveillance echocardiography and risk-directed management in patients at risk of future rVHD progression.
Study Type
OBSERVATIONAL
Enrollment
116,380
Zhongshan Hospital
Shanghai, Shanghai Municipality, China
Incident Regurgitant Valvular Heart Disease
Incident regurgitant valvular heart disease was defined as new progression to moderate or severe aortic regurgitation, mitral regurgitation, or tricuspid regurgitation on follow-up echocardiography after the index ECG-CXR assessment. For each target valve, patients with no or mild regurgitation at baseline were considered at risk, and the first follow-up echocardiographic examination showing moderate or severe regurgitation was considered an incident event.
Time frame: Up to 5 years
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.