AI-Assisted Smart Stethoscope Screening for Structural Heart Disease in School Students in Ruyang County (RY-CHD Screen)

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:

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.

Study Overview

• Status: Completed
• Conditions: Structural Heart Disease
• Intervention / Treatment: Diagnostic test: AI-Assisted Cardiac Auscultation using the HearTech Smart Stethoscope

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.

• Study Type: Observational
• Enrollment (Actual): 6614

Contacts and Locations

Study Locations

• China
  • Henan
    • Luoyang, Henan, China
      • Ruyang County People's Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

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.

Description

Inclusion Criteria:

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

Exclusion Criteria:

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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Screen group

Diagnostic test: AI-Assisted Cardiac Auscultation using the HearTech Smart Stethoscope; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	From enrollment to the end of screen at 4 months.
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.	From enrollment to the end of screen at 4 months.
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.	From enrollment to the end of screen at 4 months.

Collaborators and Investigators

• Sponsor: Heart Health Research Center

Study record dates

Study Major Dates

• Study Start (Actual): October 27, 2025
• Primary Completion (Actual): December 29, 2025
• Study Completion (Actual): January 5, 2026

Study Registration Dates

• First Submitted: September 17, 2025
• First Submitted That Met QC Criteria: September 23, 2025
• First Posted (Actual): September 26, 2025

Study Record Updates

• Last Update Posted (Actual): March 3, 2026
• Last Update Submitted That Met QC Criteria: March 2, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Other Study ID Numbers: RY-Screen

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No