Rheumatic Heart DiseaseSHIELD 1NCT07599956
Artificial Intelligence to Scale Early Rheumatic Heart Disease Detection
A study testing AI assisted echocardiography in people with Rheumatic Heart Disease, run by Children's Hospital Medical Center, Cincinnati at 1 site in Uganda.
Trial summary
The main goal of this project is to see if RADAR (Rapid AI-assisted Detection and Analysis of Rheumatic heart disease), which is a machine and deep-learning AI model, can help make rheumatic heart disease (RHD) screening easier to expand. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Rheumatic Heart Disease
- What is being tested?
- AI assisted echocardiography
- Type of treatment
- Pill or oral medicine
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 62 participants
- Where
- 1 siteUganda
- Study dates
- Nov 2026to Jun 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- Employed at a participating ADUNU facility
- Holds a designated role in the ADUNU program as a nurse screener
Who cannot join
- None. The pragmatic trial design includes all eligible staff at participating facilities.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Uganda1 site
Uganda Heart Institute
Kampala
Doreen Nakagaayi, +256 780770785, dnakagaayi@gmail.com
Doreen Nakagaayi
About this study
The main goal of this project is to see if RADAR (Rapid AI-assisted Detection and Analysis of Rheumatic heart disease), which is a machine and deep-learning AI model, can help make rheumatic heart disease (RHD) screening easier to expand. Specifically, the project will test whether RADAR can screen as accurately-or more accurately-than current methods, and whether it can be used effectively in different low-resource settings. The aim is to show that RADAR could be adopted and used widely around the world.
- Conditions
- Rheumatic Heart Disease
- Being tested
- AI assisted echocardiography
- Keywords
- Rheumatic heart disease, Artificial Intelligence, Deep Learning, Machine Learning
- Medical subject headings
- Rheumatic Heart Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI assisted echocardiographyDiagnostic test
Continue standard of care with AI-assisted echocardiography
| Study group | Role | What they receive |
|---|---|---|
| Standard non-AI echocardiography | No intervention | In the Standard non-AI Echocardiography arm, participants will receive the current standard of care under the ADUNU program, which includes a single parasternal long-axis view with black-and-white and color Doppler imaging. Providers have been trained to recognize mitral regurgitation greater than 1.5 or 2 cm, any aortic insufficiency, qualitatively reduced left ventricular systolic function, and pericardial effusion. Detection of any of these findings constitutes a screen positive, prompting referral for a confirmatory echocardiogram. |
| RADAR-AI-assisted echocardiography | Experimental | In the RADAR Echocardiography arm, participants will undergo AI-assisted screening according to the well-established RADAR protocol including the same image acquisition protocol but interpreted by the tablet-based software based on two independent AI algorithms 1) RHD positive or negative and 2) mitral regurgitation jet length. Positive findings from either algorithm constitutes a screen positive. Providers may also refer for other concerns. Receives: Diagnostic Test: AI assisted echocardiography |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of Provider RHD Screening
The number of correctly identified (positive or negative) screenings divided by the total number of exams.
Measured: 1 year
Secondary outcomes (1)
Interpretation Sensitivity
The number of correctly identified positive screening exams divided by the sum of correctly identified positive and incorrectly identified negative exams.
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 May 2026
- Study startNov 2026 (estimated)
- Primary completionJun 2028 (estimated)
- Study completionJun 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Rheumatic 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Following informed consent, providers will be randomized using the computer-generated online randomization module in REDCap, housed at Cincinnati Children's. Randomization will use permuted blocks with no stratification. Of the 52 providers enrolled, 26 will be assigned to each study arm-AI-assisted echocardiography or standard non-AI echocardiography-in a 1:1 ratio.
- Masking
- Single blind
- Who is masked
- Care provider
- Enrolment
- 62 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Children's Hospital Medical Center, Cincinnati
- Sponsor type
- University, hospital or other
- Collaborators
- Uganda Heart Institute, Ochsner Health System, Vanderbilt University Medical Center, Children's National Health Center
- Responsible party
- Sponsor
- Investigators
- Andrea Beaton, Principal investigator, Children's Hospital Medical Center, Cincinnati
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07599956
- Sponsor's protocol ID
- 2026-0304
- Acronym
- SHIELD 1
- Status last verified
- Oct 2026
- First submitted
- 14 May 2026
- Last updated
- 16 Oct 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 16 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence to Scale Early Rheumatic Heart Disease Detection
- ClinicalTrials.gov ID
- NCT07599956
- Acronym / sponsor ID
- SHIELD 1 / 2026-0304
- Conditions
- Rheumatic Heart Disease
- Keywords
- Rheumatic heart disease, Artificial Intelligence, Deep Learning, Machine Learning
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 62 participants (estimated)
- Lead sponsor
- Children's Hospital Medical Center, CincinnatiUniversity, hospital or other
- Collaborators
- Uganda Heart Institute, Ochsner Health System, Vanderbilt University Medical Center, Children's National Health Center
- Study start
- Nov 2026 (estimated)
- Primary completion
- Jun 2028 (estimated)
- Study completion
- Jun 2028 (estimated)
- First posted
- 20 May 2026 (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 main goal of this project is to see if RADAR (Rapid AI-assisted Detection and Analysis of Rheumatic heart disease), which is a machine and deep-learning AI model, can help make rheumatic heart disease (RHD) screening easier to expand. Specifically, the project will test whether RADAR can screen as accurately-or more accurately-than current methods, and whether it can be used effectively in different low-resource settings. The aim is to show that RADAR could be adopted and used widely around the world.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (care provider)
- Number of arms
- 2
- Model description
- Following informed consent, providers will be randomized using the computer-generated online randomization module in REDCap, housed at Cincinnati Children's. Randomization will use permuted blocks with no stratification. Of the 52 providers enrolled, 26 will be assigned to each study arm-AI-assisted echocardiography or standard non-AI echocardiography-in a 1:1 ratio.
| Arm | Type | Receives |
|---|---|---|
| Standard non-AI echocardiography | No intervention | –In the Standard non-AI Echocardiography arm, participants will receive the current standard of care under the ADUNU program, which includes a single parasternal long-axis view with black-and-white and color Doppler imaging. Providers have been trained to recognize mitral regurgitation greater than 1.5 or 2 cm, any aortic insufficiency, qualitatively reduced left ventricular systolic function, and pericardial effusion. Detection of any of these findings constitutes a screen positive, prompting referral for a confirmatory echocardiogram. |
| RADAR-AI-assisted echocardiography | Experimental | Diagnostic Test: AI assisted echocardiographyIn the RADAR Echocardiography arm, participants will undergo AI-assisted screening according to the well-established RADAR protocol including the same image acquisition protocol but interpreted by the tablet-based software based on two independent AI algorithms 1) RHD positive or negative and 2) mitral regurgitation jet length. Positive findings from either algorithm constitutes a screen positive. Providers may also refer for other concerns. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- Employed at a participating ADUNU facility
- Holds a designated role in the ADUNU program as a nurse screener
Key exclusion criteria (1 listed)
- None. The pragmatic trial design includes all eligible staff at participating facilities.
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 echocardiographyContinue standard of care with AI-assisted echocardiography | Diagnostic test | RADAR-AI-assisted echocardiography |
Primary outcome
Accuracy of Provider RHD Screening
Time frame: 1 year
The number of correctly identified (positive or negative) screenings divided by the total number of exams.
1 secondary outcome
Interpretation Sensitivity
Time frame: 6 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Oct 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.
Andrea Beaton principal investigator
Children's Hospital Medical Center, Cincinnati
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI assisted echocardiography in people with Rheumatic Heart Disease, run by Children's Hospital Medical Center, Cincinnati at 1 site in Uganda.
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 2 inclusion and 1 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: opening soon, as of the sponsor's last update on 16 Oct 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 Uganda. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Isabella Brigham (513-517-1307, isabella.aspromonte@cchmc.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of Provider RHD Screening (time frame: 1 year). 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 16 Oct 2026.