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NCT Number: NCT07830251

AI-Assisted Versus Independent Heart Sound Screening for Congenital Heart Disease in Children

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.

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Key information

Conditions

Congenital Heart Disease (CHD) Artifical Intelligence Cardiac Auscultation Cardiovascular Abnormalities Cardiovascular Diseases Congenital Abnormalities Congenital, Hereditary, and Neonatal Diseases and Abnormalities Heart Defects, Congenital Heart Diseases Primary Care Physician Screening

Age range

0 year–18 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Qinghai Provincial Women and Children's Hospital

Qinghai, China

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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.

Exclusion criteria

  • 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.

Treatment and study plan

AI-Assisted Cardiac Auscultation

Other

During 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.

Primary outcomes

  1. Sensitivity for Detecting Congenital Heart Disease Requiring Clinical Intervention

    Time frame: From enrollment to the end of treatment at 6 months

Secondary outcomes

  1. Specificity for Detecting Congenital Heart Disease Requiring Clinical Intervention

    Time frame: From enrollment to the end of treatment at 6 months

  2. Sensitivity for Detecting All Congenital Heart Disease

    Time frame: From enrollment to the end of treatment at 6 months

  3. Positive Predictive Value for Detecting Congenital Heart Disease Requiring Clinical Intervention

    Time frame: From enrollment to the end of treatment at 6 months

  4. Referral Completion Rate

    Time frame: From the initial screening visit through completion of the protocol-specified referral follow-up at 9 months

  5. Confirmed Diagnosis Rate After Referral

    Time frame: From the initial screening visit through completion of the protocol-specified referral follow-up at 9 months

Study contacts

Contact information is provided by the study sponsor or research team.

Liudan Zhao

CONTACT

[email protected]

0086-18368407858

Sponsors and collaborators

Lead sponsor

Kun Sun

Other

Collaborators

  • Bill and Melinda Gates Foundation
  • Women and Children Hospital of Qinghai Province

Registry information

Official study title

A Prospective, School-Based, Cluster-Randomized Controlled Trial Comparing AI-Assisted Versus Independent Cardiac Auscultation by Primary Care Physicians for Detecting Congenital Heart Disease in Qinghai Province, China

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Sep 21, 2026
Registry last updated
Sep 21, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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