AI could help predict risks for kids after heart surgery
NCT ID NCT07375602
First seen Jun 24, 2026 · Last updated Aug 06, 2026 · Updated 3 times
Summary
This study aims to create an artificial intelligence (AI) model that can predict complications in children who have a common heart defect called a ventricular septal defect (VSD) repaired with a catheter-based procedure. Researchers will analyze data from over 5,000 children's medical records, including lab results, images, and text reports. The goal is to see if the AI can accurately identify which children are at higher risk for problems like irregular heartbeats or valve issues after the procedure.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- What this could lead to
- If successful, this could lead to a tool that helps doctors better predict which children are at risk for complications after heart surgery, allowing for more personalized care.
- What could go wrong
- This is an observational study, not a treatment trial. The AI model may not be accurate enough for real-world use, and results may not apply to all hospitals or patients.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Study facts
What this study's own registry entry says, in plain language.
- Participants
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About 5,249 people
The number the study aims to enrol. It can still change while the study runs.
- Started
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Feb 2026
- Expected to finish
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Dec 2027
An estimate. End dates often move.
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Children (18 years or younger) with echocardiography-confirmed perimembranous ventricular septal defect who underwent transcatheter device closure at Xinhua Hospital between January 1, 2015, and December 31, 2025, identified retrospectively from routine clinical care records.
- Ages
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Up to 18 years
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: * Age ≤ 18 years at the time of transcatheter procedure. * Diagnosis of perimembranous ventricular septal defect confirmed by echocardiography, and underwent transcatheter device closure at the study center. * Medical records sufficient to ascertain the primary outcome within the pre-specified follow-up window, and availability of minimum baseline clinical information required for model development/validation. Exclusion Criteria: * Ventricular septal defects not classified as perimembranous on echocardiography, including muscular, outlet, or inlet VSDs, as well as multiple or complex VSDs involving more than one septal region. * Presence of complex congenital heart disease or associated structural abnormalities requiring concomitant surgical repair (e.g., tetralogy of Fallot). * Prior surgical VSD repair or prior transcatheter VSD closure.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
1 site. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
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Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
RECRUITINGShanghai, Shanghai Municipality, 200092, China
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