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Structural Heart DiseaseRY-CHD ScreenNCT07194785

AI-Assisted Smart Stethoscope Screening for Structural Heart Disease in School Students in Ruyang County

An observational study of Structural Heart Disease, run by Heart Health Research Center at 1 site in China.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record

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Trial summary

The goal of this observational diagnostic study is to evaluate whether an artificial intelligence (AI)-enabled smart stethoscope can accurately detect structural heart disease in school-aged children and adolescents (10-18 years) in Ruyang County, China. Read more about this study

Who is it for?
Ages 10 to 18 yearsHealthy volunteers can take part
Conditions the study is for
Structural Heart Disease
What is being tested?
AI-Assisted Cardiac Auscultation using the HearTech Smart Stethoscope
How many people
6,614 participants
Where
1 siteChina
Study dates
27 Oct 2025to 5 Jan 2026
How long will I take part?
7 Days
Phase
Observational

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 10 to 18 years
  • All sexes
  • Healthy volunteers accepted
  • Child, Adult

Study population: Participants will be recruited from primary and secondary schools in Ruyang County, Henan Province, China. Screening will be conducted on-site at schools by trained personnel using AI-enabled smart stethoscopes. Students identified as having abnormal findings will be referred to the Cardiology Department of Ruyang County People's Hospital for confirmatory transthoracic echocardiography. A subset of students with normal screening results will also undergo echocardiography to estimate false-negative rates.

Who may be able to join

  • School students aged 10-18 years.
  • Able to cooperate with cardiac auscultation.
  • Student and parent/guardian provide written informed consent.

Who cannot join

  • Student or parent/guardian declines participation.
  • Inability or unwillingness to follow screening procedures or cooperate with cardiac auscultation.
  • Refusal to undergo standard transthoracic echocardiography or cardiology evaluation.
  • Previously diagnosed structural heart disease.
  • Chest wall deformities or skin conditions that may interfere with auscultation.
  • Fever ≥37.5 °C on the day of examination, or severe developmental delay or other conditions preventing cooperation with the examination.

Trial locations and contacts

1 site in 1 country.

China1 site
  • Ruyang County People's Hospital

    Luoyang, Henan

Other trials in China

About this study

Official title: Screening Program for Structural Heart Disease Among Primary and Secondary School Students in Ruyang County

The goal of this observational diagnostic study is to evaluate whether an artificial intelligence (AI)-enabled smart stethoscope can accurately detect structural heart disease in school-aged children and adolescents (10-18 years) in Ruyang County, China.

The main questions it aims to answer are:

Read more

Can the smart stethoscope reliably identify students with cardiac murmurs that indicate possible structural heart disease? How well do the sensitivity, specificity, and predictive values of the smart stethoscope compare with standard echocardiography?

Researchers will compare AI-assisted stethoscope screening results with echocardiography (gold standard) to see if the device can be used as an effective early screening tool.

Participants will:

Undergo a heart sound screening using the AI-enabled smart stethoscope (3-5 minutes).

If screening is positive, receive a free echocardiogram at Ruyang County People's Hospital.

A small sample of students with negative screening results will also receive echocardiography to check for missed cases.

Read the detailed description

Structural heart disease (SHD), including congenital and acquired cardiac abnormalities, is a leading cause of morbidity in children and adolescents. Cardiac murmurs are common clinical signs, but traditional auscultation has limited accuracy in school or community settings due to examiner variability and limited access to echocardiography.

This study evaluates the performance of an artificial intelligence (AI)-enabled smart stethoscope for school-based screening of SHD in primary and secondary students in Ruyang County, China. The device integrates high-sensitivity acoustic sensors, noise-reduction technology, and deep learning algorithms to provide automated interpretations of heart sounds within seconds. Prior validation studies have demonstrated high sensitivity (>80%) and specificity (>90%) for congenital heart disease and up to 94% sensitivity and 98% specificity for rheumatic heart disease.

Screening will be conducted by trained personnel at four standard cardiac auscultation sites. Students with abnormal AI findings will undergo repeat testing and, if confirmed, will be referred for transthoracic echocardiography at Ruyang County People's Hospital. A subset of students with negative AI screens will also receive echocardiography to estimate false-negative rates.

Data will be analyzed using 2×2 contingency tables to compare AI screening results with echocardiography, and diagnostic performance metrics including sensitivity, specificity, positive predictive value, and negative predictive value will be calculated with 95% confidence intervals. Agreement between AI-assisted auscultation and echocardiography will be assessed using Cohen's kappa.

This study will provide evidence on the feasibility, accuracy, and scalability of AI-enabled smart stethoscopes for early SHD detection in school-based, low-resource settings.

Being tested
AI-Assisted Cardiac Auscultation using the HearTech Smart Stethoscope

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • AI-Assisted Cardiac Auscultation using the HearTech Smart StethoscopeDiagnostic test

    This intervention utilizes the HearTech smart stethoscope, where trained research personnel perform standardized examinations of four cardiac auscultation areas on subjects. The integrated AI algorithm analyzes heart sounds in real time and automatically generates reports. An initial positive detection triggers a repeat testing process, with the algorithm ultimately determining a positive screening result based on three detection outcomes (any two positive). This AI-assisted auscultation system is designed to achieve large-scale, standardized, and highly efficient preliminary heart murmur screening.

Study groups in NCT07194785
Study groupRoleWhat they receive
Screen groupNot described
Receives: Diagnostic Test: AI-Assisted Cardiac Auscultation using the HearTech Smart Stethoscope

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Specificity of AI-enabled smart stethoscope

    Proportion of students with a "screening negative" report by the smart stethoscope who are confirmed to have no structural heart disease by transthoracic echocardiography.

    Measured: From enrollment to the end of screen at 4 months.

  2. Positive Predictive Value (PPV) of AI-enabled smart stethoscope

    Proportion of students with two consecutive "screening positive" reports by the smart stethoscope who are confirmed to have structural heart disease by echocardiography.

    Measured: From enrollment to the end of screen at 4 months.

  3. Negative Predictive Value (NPV) of AI-enabled smart stethoscope

    Proportion of a random subset of students with a "screening negative" report by the smart stethoscope who are confirmed to have no structural heart disease by echocardiography.

    Measured: From enrollment to the end of screen at 4 months.

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted26 Sep 2025
  2. Study start27 Oct 2025
  3. Primary completion29 Dec 2025
  4. Study completion5 Jan 2026

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
6,614 participants (actual)
Target duration
7 Days
IDs, dates and publications
ClinicalTrials.gov ID
NCT07194785
Sponsor's protocol ID
RY-Screen
Acronym
RY-CHD Screen
Status last verified
Mar 2026
First submitted
17 Sep 2025
Last updated
3 Mar 2026
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

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