Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Uganda Heart Institute | OTHER |
| Ochsner Health System | OTHER |
| Vanderbilt University Medical Center | OTHER |
| Children's National Health Center |
Not provided
Not provided
Not provided
Not provided
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.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI assisted echocardiography | Diagnostic Test | Continue standard of care with AI-assisted echocardiography |
|
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of Provider RHD Screening | The number of correctly identified (positive or negative) screenings divided by the total number of exams. | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Interpretation Sensitivity | The number of correctly identified positive screening exams divided by the sum of correctly identified positive and incorrectly identified negative exams. | 6 months |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Isabella Brigham | Contact | 513-517-1307 | isabella.aspromonte@cchmc.org |
| Name | Affiliation | Role |
|---|---|---|
| Andrea Beaton | Children's Hospital Medical Center, Cincinnati | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Uganda Heart Institute | Kampala | Uganda |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D012214 | Rheumatic Heart Disease |
| ID | Term |
|---|---|
| D012213 | Rheumatic Fever |
| D013290 | Streptococcal Infections |
| D016908 | Gram-Positive Bacterial Infections |
| D001424 | Bacterial Infections |
Not provided
Not provided
| UNKNOWN |
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.
Not provided
Not provided
Cardiologists who make up the adjudication panel.
| D001423 | Bacterial Infections and Mycoses |
| D007239 | Infections |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |