The goal of this observational study is to develop and validate a multimodal artificial intelligence prediction model for treatment-related complications in children with perimembranous ventricular septal defect (pmVSD) undergoing transcatheter device closure. The main question it aims to answer is: Can an AI model that integrates demographics, laboratory results, electronic health record text, echocardiography reports, chest radiographs, and electrocardiogram accurately predict the risk of complications at the individual patient level? Data will be retrospectively collected from routine clinical care records of pediatric patients who underwent transcatheter closure for pmVSD. Deep learning methods will be used to extract features from text and images to train and validate the prediction model.
Study Type
OBSERVATIONAL
Enrollment
5,249
Composite Procedure-Related Complications After Transcatheter Closure of Perimembranous VSD
Occurrence of a composite endpoint of procedure-related complications, including arrhythmia requiring treatment, new-onset or worsened valvular regurgitation, residual shunt requiring reintervention, and device embolization.
Time frame: Up to 30 Days After Transcatheter Closure
Area Under the Precision-Recall Curve (AUCPR) for Complication Prediction
The area under the precision-recall curve (AUCPR) of the model for predicting the primary composite procedure-related complication endpoint.
Time frame: Up to 30 Days After Transcatheter Closure
Sensitivity of the Model at a Pre-Specified Risk Threshold
Sensitivity for predicting the primary composite procedure-related complication endpoint at a pre-specified probability (risk) threshold.
Time frame: Up to 30 Days After Transcatheter Closure
Positive Predictive Value (PPV) of the Model at a Pre-Specified Risk Threshold
Positive predictive value (PPV) for predicting the primary composite procedure-related complication endpoint at the same pre-specified probability (risk) threshold.
Time frame: Up to 30 Days After Transcatheter Closure
Negative Predictive Value (NPV) of the Model at a Pre-Specified Risk Threshold
Negative predictive value (NPV) for predicting the primary composite procedure-related complication endpoint at the same pre-specified probability (risk) threshold.
Time frame: Up to 30 Days After Transcatheter Closure
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