This is a prospective, school-based, cluster-randomized controlled trial conducted in Qinghai Province, China. The study will evaluate whether artificial intelligence (AI) can help primary care physicians identify congenital heart disease (CHD) during large-scale screening of children and adolescents.
Eligible schools, rather than individual participants, will be randomly assigned to one of two screening approaches: independent cardiac auscultation by primary care physicians or AI-assisted cardiac auscultation. In both groups, primary care physicians will perform cardiac auscultation and record heart sounds. In the AI-assisted group, the physicians will also receive AI analysis of the recorded heart sounds to support their final screening decision.
Participants will undergo medical history collection, cardiac auscultation, heart-sound recording, and echocardiography. Echocardiography and expert review will serve as the reference standard. The primary outcome is the sensitivity of each screening approach for detecting CHD that may require clinical intervention or specialist management. The study will also assess detection of all CHD, referral completion, confirmed diagnoses after referral, and related screening outcomes.
Children and adolescents aged 0-18 years who are enrolled in a participating school in Qinghai Province and are eligible for the school-based congenital heart disease screening program.
Written informed consent provided by the parent or legal guardian, or ethics-approved electronic informed consent, with participant assent obtained when applicable.
Ability to undergo the protocol-specified cardiac auscultation, heart-sound recording, and echocardiographic assessment.
Participant and/or parent or legal guardian is willing to provide the required medical history and, if referral is recommended, follow-up information.
Inability to cooperate with cardiac auscultation, heart-sound recording, or echocardiography, when the required procedure cannot be completed after reasonable attempts.
Known congenital heart disease previously treated with catheter-based intervention or cardiac surgery, when the primary endpoint is not applicable under the protocol.
Any condition that prevents completion of the required study procedures or prevents obtaining an interpretable protocol-specified echocardiographic assessment.
Informed consent or assent is not provided, or consent is withdrawn before completion of the study procedures.
Parallel
AI-Assisted Cardiac Auscultation
Other interventionDuring the school-based screening visit, a trained primary care physician will perform standardized cardiac auscultation and record the participant's heart sounds. The recorded heart sounds will be analyzed by an artificial intelligence-assisted auscultation system, which will provide automated analysis and decision-support feedback to the physician. The physician will consider the AI output together with the clinical examination and make the final screening and referral decision. The AI output is not a definitive diagnosis and will not replace echocardiography or specialist evaluation. No medication, surgery, or other therapeutic treatment will be administered as part of this intervention.
Sensitivity for Detecting Congenital Heart Disease Requiring Clinical Intervention
Specificity for Detecting Congenital Heart Disease Requiring Clinical Intervention
Sensitivity for Detecting All Congenital Heart Disease
Positive Predictive Value for Detecting Congenital Heart Disease Requiring Clinical Intervention
Referral Completion Rate
Map coordinates are unavailable for these locations. Locations are shown below instead.
ChinaClick on the lead sponsor to view all of their trials.
Kun Sun
Lead sponsor
Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Sponsor institution
Bill and Melinda Gates Foundation
Collaborator
Women and Children Hospital of Qinghai Province
Collaborator
This trial is not recruiting at the moment. You can still explore other options:
