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"SOUND" Trial: Study of On-site Use of Novel AI-assisted Diagnostics in CHD Screening

NCT06791109 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 19697

Last updated 2026-04-07

No results posted yet for this study

Summary

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.

Conditions

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

Interventions

DIAGNOSTIC_TEST

Primary care physicians

For participants in Group A, a nonblinded independent staff member will first collect medical history, followed by sequential auscultation and CHD assessment by a specialist physician and a primary care physician, with an echocardiogram performed last.

DIAGNOSTIC_TEST

AI + Primary care physicians

For participants in Group B, after medical history collection, both a specialist physician and a primary care physician will perform auscultation and CHD assessment. Subsequently, the primary care physician will use an electronic stethoscope to collect heart sound data according to the protocol and upload the recordings to a cloud platform. The AI model will analyze the data on the cloud platform and provide a diagnostic result within 5-10 seconds for the primary care physician's reference. The primary care physician may reassess the findings based on the AI model's feedback, and the participant will then undergo an echocardiogram.

Sponsors & Collaborators

  • Bill and Melinda Gates Foundation

    collaborator OTHER

  • Kun Sun

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
NONE
Model
PARALLEL

Eligibility

Max Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-09-22
Primary Completion
2025-11-18
Completion
2026-01-04

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06791109 on ClinicalTrials.gov