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Efficacy Comparison Between Independent Auscultation by Primary Care Physicians and AI-Assisted Auscultation in Large-scale Screening for Congenital Heart Disease: A Cluster Randomized Controlled Trial in China

K

Kun Sun

Status

Enrolling

Conditions

Auscultation for Clinical Evaluation
Cluster Randomized Trial
Screening Tool
Congenital Heart Disease (CHD)
Artificial Intelligence (AI)

Treatments

Diagnostic Test: Primary care physicians
Diagnostic Test: AI + Primary care physicians

Study type

Interventional

Funder types

Other

Identifiers

NCT06791109
INV-072724 (Other Grant/Funding Number)
XHEC-C-2025-013-1

Details and patient eligibility

About

This study plans to conduct clinical validation of the model in real clinical settings, comparing it with primary care physicians and specialist physicians to ensure the model's practicality. Through continuous optimization and practice, the study aims to use AI-assisted heart sound auscultation to empower the auscultation capabilities of primary care obstetricians, pediatricians, and non-cardiovascular specialists nationwide. This will not only reduce the missed diagnosis rate and improve the detection rate of existing CHD screenings, but also expand the coverage of current CHD screening networks, incorporating newborns, infants, preschool children, children, and adolescents aged 0-18 years into the screening scope. The study aims to establish a new benchmark in child health management by providing feasible and cost-effective child health management solutions for other developing countries, contributing to global efforts for the health of children.

Enrollment

28,833 estimated patients

Sex

All

Ages

Under 18 years old

Volunteers

Accepts Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria (Schools):

  • The school is of the type: kindergarten, primary school, junior high school, or senior high school.
  • The school has medical screening facilities and conditions that can support AI-assisted screening.
  • The area where the school is located has at least one primary healthcare institution willing to participate in this trial.
  • The school's management and teaching staff are willing to participate in the study and can cooperate to complete the related screening and data collection work.

Exclusion Criteria (Schools):

  • More than half of the students in the school refuse to participate in the trial.
  • Schools that are unable to complete the study due to severe limitations in geographical location and transportation conditions.
  • Schools lacking medical screening facilities and conditions necessary for the implementation of screening.
  • Areas where there are no primary healthcare institutions willing to participate in this trial.
  • Schools whose management and teaching staff refuse to participate in the study or are unable to cooperate in completing the related screening and data collection work.

Inclusion Criteria (Individuals):

  • Children aged between 0 and 18 years, regardless of gender.
  • Children who agree to undergo echocardiography to determine the presence of congenital heart disease.
  • Individuals who voluntarily participate in this study and sign the informed consent form.

Exclusion Criteria (Individuals):

  • Individuals over the age of 18.
  • Children who are unable to complete echocardiography or do not cooperate with auscultation.
  • Participants who are unable to provide informed consent or are unwilling to comply with the study requirements to provide medical data for further analysis and research.
  • Participants who have received interventional or surgical treatment for CHD.

Trial design

Primary purpose

Screening

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

28,833 participants in 2 patient groups

Primary care physicians
Active Comparator group
Treatment:
Diagnostic Test: Primary care physicians
AI + Primary care physicians
Experimental group
Treatment:
Diagnostic Test: AI + Primary care physicians

Trial contacts and locations

1

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Central trial contact

Kun Sun, Phd

Data sourced from clinicaltrials.gov

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