Artificial Intelligence to Scale Early Rheumatic Heart Disease Detection

Status

Not yet recruiting

Phases

Unknown

Study type

Interventional

Source

ClinicalTrials.gov

Registry ID

NCT07599956

Acronym

SHIELD 1

Enrollment

Registered

2026-05-20

Start date

2026-06-01

Completion date

2028-06-01

Last updated

2026-05-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Rheumatic Heart Disease

Keywords

Rheumatic heart disease, Artificial Intelligence, Deep Learning, Machine Learning

Brief 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. 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.

Interventions

DIAGNOSTIC_TESTAI assisted echocardiography

Continue standard of care with AI-assisted echocardiography

Study design

Allocation

RANDOMIZED

Intervention model

PARALLEL

Primary purpose

DIAGNOSTIC

Masking

SINGLE (Caregiver)

Masking description

Cardiologists who make up the adjudication panel.

Intervention 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.

Eligibility

Sex/Gender

ALL

Healthy volunteers

Yes

Inclusion criteria

* Employed at a participating ADUNU facility * Holds a designated role in the ADUNU program as a nurse screener

Exclusion criteria

* None. The pragmatic trial design includes all eligible staff at participating facilities.

Design outcomes

Primary

Measure	Time frame	Description
Accuracy of Provider RHD Screening	1 year	The number of correctly identified (positive or negative) screenings divided by the total number of exams.

Secondary

Measure	Time frame	Description
Interpretation Sensitivity	6 months	The number of correctly identified positive screening exams divided by the sum of correctly identified positive and incorrectly identified negative exams.

Countries

Uganda

Contacts

CONTACTIsabella Brigham

isabella.aspromonte@cchmc.org513-517-1307

PRINCIPAL_INVESTIGATORAndrea Beaton

Children's Hospital Medical Center, Cincinnati

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: May 28, 2026