[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100640746":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":25,"centralContacts":29,"locations":35,"responsibleParty":53,"collaborators":55,"id":64,"slug":65,"hasResults":66,"nctId":67,"briefTitle":68,"officialTitle":68,"acronym":69,"eligibilityCriteria":70,"healthyVolunteers":71,"sex":72,"minAge":12,"maxAge":12,"enrollmentInfo":73,"targetDuration":12,"studyType":76,"phases":77,"briefSummary":79,"conditions":80,"keywords":82,"overallStatus":87,"whyStopped":12,"lastUpdateSubmitDate":88,"lastUpdatePostDateStruct":89,"startDateStruct":92,"completionDateStruct":94,"leadSponsor":96,"locationsCount":97},{"fullName":5,"class":6},"Children's Hospital Medical Center, Cincinnati","OTHER",[8,13],{"label":9,"type":10,"description":11,"interventionNames":12},"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.",null,{"label":14,"type":15,"description":16,"interventionNames":17},"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.",[18],"Diagnostic Test: AI assisted echocardiography",[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":12},"DIAGNOSTIC_TEST","AI assisted echocardiography","Continue standard of care with AI-assisted echocardiography",[14],[26],{"name":27,"affiliation":5,"role":28},"Andrea Beaton","PRINCIPAL_INVESTIGATOR",[30],{"name":31,"role":32,"phone":33,"phoneExt":12,"email":34},"Isabella Brigham","CONTACT","513-517-1307","isabella.aspromonte@cchmc.org",[36],{"facility":37,"status":12,"city":38,"state":12,"zip":12,"country":39,"countryCode":40,"cosmosGeoPoint":41,"geoPoint":46,"contacts":47},"Uganda Heart Institute","Kampala","Uganda","UG",{"type":42,"coordinates":43},"Point",[44,45],32.58219,0.31628,{"lat":45,"lon":44},[48,52],{"name":49,"role":32,"phone":50,"phoneExt":12,"email":51},"Doreen Nakagaayi","+256 780770785","dnakagaayi@gmail.com",{"name":49,"role":28,"phone":12,"phoneExt":12,"email":12},{"type":54,"investigatorFullName":12,"investigatorTitle":12,"investigatorAffiliation":12,"oldNameTitle":12,"oldOrganization":12},"SPONSOR",[56,57,59,61],{"name":37,"class":6},{"name":58,"class":6},"Ochsner Health System",{"name":60,"class":6},"Vanderbilt University Medical Center",{"name":62,"class":63},"Children's National Health Center","UNKNOWN","100640746","artificial-intelligence-to-scale-early-rheumatic-heart-disease-detection-100640746",false,"NCT07599956","Artificial Intelligence to Scale Early Rheumatic Heart Disease Detection","SHIELD 1","Inclusion Criteria:\n\n* Employed at a participating ADUNU facility\n* Holds a designated role in the ADUNU program as a nurse screener\n\nExclusion Criteria:\n\n* None. The pragmatic trial design includes all eligible staff at participating facilities.",true,"ALL",{"count":74,"type":75},62,"ESTIMATED","INTERVENTIONAL",[78],"NA","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.",[81],"Rheumatic Heart Disease",[83,84,85,86],"Rheumatic heart disease","Artificial Intelligence","Deep Learning","Machine Learning","NOT_YET_RECRUITING","2026-05-22",{"date":90,"type":91},"2026-05-27","ACTUAL",{"date":93,"type":75},"2026-06",{"date":95,"type":75},"2028-06",{"name":5,"class":6},1]