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.
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
- Are there results?
- None posted in the registry
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.
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.
- Conditions
- Structural Heart Disease
- 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 group | Role | What they receive |
|---|---|---|
| Screen group | Not 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.
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.
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.
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.
- First posted26 Sep 2025
- Study start27 Oct 2025
- Primary completion29 Dec 2025
- Study completion5 Jan 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Structural Heart DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
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
Sponsor and investigators
- Lead sponsor
- Heart Health Research Center
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
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
Study at a glance
From the registry record, last updated by the sponsor on 3 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Screening Program for Structural Heart Disease Among Primary and Secondary School Students in Ruyang County
- ClinicalTrials.gov ID
- NCT07194785
- Acronym / sponsor ID
- RY-CHD Screen / RY-Screen
- Conditions
- Structural Heart Disease
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 6,614 participants (actual)
- Lead sponsor
- Heart Health Research CenterUniversity, hospital or other
- Study start
- 27 Oct 2025 (actual)
- Primary completion
- 29 Dec 2025 (actual)
- Study completion
- 5 Jan 2026 (actual)
- First posted
- 26 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 7 Days
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Screen group | – | Diagnostic Test: AI-Assisted Cardiac Auscultation using the HearTech Smart Stethoscope |
Who may qualify
- Ages
- 10 to 18 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- 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.
Key inclusion criteria (3 listed)
- School students aged 10-18 years.
- Able to cooperate with cardiac auscultation.
- Student and parent/guardian provide written informed consent.
Key exclusion criteria (6 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted Cardiac Auscultation using the HearTech Smart StethoscopeThis 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. | Diagnostic test | Screen group |
Primary outcome
Specificity of AI-enabled smart stethoscope
Time frame: From enrollment to the end of screen at 4 months.
Proportion of students with a "screening negative" report by the smart stethoscope who are confirmed to have no structural heart disease by transthoracic echocardiography.
Positive Predictive Value (PPV) of AI-enabled smart stethoscope
Time frame: From enrollment to the end of screen at 4 months.
Proportion of students with two consecutive "screening positive" reports by the smart stethoscope who are confirmed to have structural heart disease by echocardiography.
Negative Predictive Value (NPV) of AI-enabled smart stethoscope
Time frame: From enrollment to the end of screen at 4 months.
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.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Mar 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Structural Heart Disease, run by Heart Health Research Center at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 3 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Specificity of AI-enabled smart stethoscope (time frame: From enrollment to the end of screen at 4 months.). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 3 Mar 2026.