Early Warning of Structural Complications in Perimembranous VSD

NCT07662343 | Active Not Recruiting DMC

• 1 other identifier: XHEC-C-2026-099
• Study Type: observational
• Target: 11,683
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to develop and test a AI-based prediction model for children with perimembranous ventricular septal defect, also called PMVSD. PMVSD is a type of hole between the lower chambers of the heart. Some children with PMVSD may later develop heart structure problems, such as aortic valve prolapse or leakage, subaortic fibrous ridge, left ventricle-to-right atrium shunt, or right ventricular outflow tract obstruction. This study will use past medical records and echocardiography reports from children who received care at six hospitals in China between 2004 and 2022. The main questions it aims to answer are: Can information written in echocardiography reports help predict which children with PMVSD are more likely to develop heart structure problems? Can natural language processing and machine learning improve early risk prediction when used together with routine clinical information? Researchers will review existing, de-identified medical data. They will use natural language processing to turn written descriptions in echocardiography reports into data that a computer model can analyze. These descriptions may include details about the edge of the heart defect, the direction of blood flow, and the relationship between the defect and nearby heart valves. Participants will not receive any study treatment or extra tests. The study will only use information already collected during routine medical care. The prediction models will be trained and tested using data from different hospitals to see how well they work across medical centers.

Conditions

Congenital Heart Disease (CHD); Ventricular Septal Defects (VSD)

Outcome Measures

Primary Outcomes (1)

• Occurrence of Perimembranous Ventricular Septal Defect Related Structural Complications

  Occurrence of at least one structural complication related to perimembranous ventricular septal defect, as identified by echocardiography, including: (1) aortic valve prolapse and/or aortic regurgitation, defined as valvular leaflet displacement into the defect and/or regurgitation detected by color Doppler; (2) subaortic fibrous ridge, defined as abnormal fibrous strand or ridge-like echogenicity in the left ventricular outflow tract; (3) left ventricle-to-right atrium shunt; or (4) right ventricular outflow tract obstruction, defined as abnormal muscular bundle hypertrophy with increased Doppler flow velocity and a peak pressure gradient greater than 20 mmHg.

  From initial diagnosis through 3 years after diagnosis

Secondary Outcomes (4)

• Area Under the Precision-Recall Curve (AUCPR) for Complication Prediction

  From initial diagnosis through 3 years after diagnosis

• Sensitivity of the Model at a Pre-Specified Risk Threshold

  From initial diagnosis through 3 years after diagnosis

• Positive Predictive Value (PPV) of the Model at a Pre-Specified Risk Threshold

  From initial diagnosis through 3 years after diagnosis

• Negative Predictive Value (NPV) of the Model at a Pre-Specified Risk Threshold

  From initial diagnosis through 3 years after diagnosis

Study Arms (2)

Training cohort

Participants from the multicenter retrospective dataset used for model development. Unstructured echocardiographic text and clinical data from this cohort will be used for feature extraction, model training, and internal optimization to establish an early warning model for structural complications related to perimembranous ventricular septal defect.

Validaction cohort

An independent subset of participants from the multicenter retrospective dataset used for model validation. Data from this cohort will be used to evaluate the discrimination, calibration, and generalizability of the developed early warning model for structural complications related to perimembranous ventricular septal defect.

Eligibility Criteria

• Age: 0 Years - 14 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17)
• Sampling Method: Non-Probability Sample

Study Population

Pediatric patients with perimembranous ventricular septal defect evaluated at six tertiary referral centers between 2004 and 2022.

You may qualify if:

• Children aged 14 years or younger at the time of presentation/diagnosis;
• Confirmed diagnosis of perimembranous ventricular septal defect (PMVSD), or PMVSD accompanied by minor cardiac anomalies that do not alter the hemodynamic status of the VSD, including small patent foramen ovale, atrial septal defect, patent ductus arteriosus, or persistent left superior vena cava;
• Availability of at least two consecutive follow-up records, with consistency between the electronic echocardiography reports and the Hospital Information System data.

You may not qualify if:

• Age older than 14 years at diagnosis;
• Presence of complex congenital heart disease;
• Patients lost to follow-up due to inability to establish contact, resulting in an indeterminate clinical outcome.

Sponsors & Collaborators

• Xinhua Hospital, Shanghai Jiao Tong University School of Medicine: lead

Study Sites (1)

Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine

Shanghai, Shanghai Municipality, 200092, China

Location

MeSH Terms

Conditions

Heart Defects, Congenital; Heart Septal Defects, Ventricular

Condition Hierarchy (Ancestors)

Cardiovascular Abnormalities; Cardiovascular Diseases; Heart Diseases; Congenital Abnormalities; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Heart Septal Defects

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Department of Pediatric Cardiology

Study Record Dates

• First Submitted: June 1, 2026
• First Posted: June 23, 2026
• Study Start: January 1, 2004
• Primary Completion: January 1, 2022
• Study Completion (Estimated): July 1, 2027
• Last Updated: June 23, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)