[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100608144":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":15,"centralContacts":19,"locations":29,"responsibleParty":50,"collaborators":53,"id":56,"slug":57,"hasResults":58,"nctId":59,"briefTitle":60,"officialTitle":61,"acronym":62,"eligibilityCriteria":63,"healthyVolunteers":58,"sex":64,"minAge":65,"maxAge":10,"enrollmentInfo":66,"targetDuration":10,"studyType":69,"phases":10,"briefSummary":70,"conditions":71,"keywords":78,"overallStatus":32,"whyStopped":10,"lastUpdateSubmitDate":86,"lastUpdatePostDateStruct":87,"startDateStruct":90,"completionDateStruct":92,"leadSponsor":94,"locationsCount":95},{"fullName":5,"class":6},"Columbia University","OTHER",[8,12],{"label":9,"type":10,"description":11,"interventionNames":10},"Intervention Group",null,"Studies meeting the following criteria will undergo adjudication by an expert panel: Moderate, moderate-severe, or severe mitral, aortic, or tricuspid regurgitation by physician or AI model assessment.\n\nDiscrepancy between physician and AI interpretations, where AI-assessed severity is greater than the physician-assessed severity (i.e. indicates that more valvular regurgitation is present)",{"label":13,"type":10,"description":14,"interventionNames":10},"Control Group","A stratified random sample of cases will be selected to match the distribution of AI-flagged cases by physician-assessed valvular regurgitation severity and will undergo the same expert panel adjudication.",[16],{"name":17,"affiliation":5,"role":18},"Pierre A Elias, MD","PRINCIPAL_INVESTIGATOR",[20,25],{"name":21,"role":22,"phone":23,"phoneExt":10,"email":24},"Heidi S Hartman, MD","CONTACT","212-305-3068","hl2738@cumc.columbia.edu",{"name":26,"role":22,"phone":27,"phoneExt":10,"email":28},"Michelle Castillo, BS","212-305-9161","mc5067@cumc.columbia.edu",[30],{"facility":31,"status":32,"city":33,"state":33,"zip":34,"country":35,"countryCode":36,"cosmosGeoPoint":37,"geoPoint":42,"contacts":43},"Columbia University Irving Medical Center","RECRUITING","New York","10032","United States","US",{"type":38,"coordinates":39},"Point",[40,41],-74.00597,40.71427,{"lat":41,"lon":40},[44,48,49],{"name":45,"role":22,"phone":46,"phoneExt":10,"email":47},"Jeffrey Ruhl, MS","570-713-7815","hvx9001@nyp.org",{"name":26,"role":22,"phone":27,"phoneExt":10,"email":28},{"name":17,"role":18,"phone":10,"phoneExt":10,"email":10},{"type":18,"investigatorFullName":51,"investigatorTitle":52,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"Pierre Elias","Assistant Professor of Medicine in the Department of Biomedical Informatics",[54],{"name":55,"class":6},"American Heart Association","100608144","delineate-prospective-100608144",false,"NCT07197736","DELINEATE-Prospective","Deep Learning for Echo Analysis, Tracking, and Evaluation Prospective Evaluation (DELINEATE-Prospective)","DELINEATE","Inclusion Criteria:\n\n* Attending cardiologist employed by Columbia University, ColumbiaDoctors, or NewYork Presbyterian Hospital who reads transthoracic echocardiograms in the Columbia echocardiography laboratory\n* Provided informed consent to take part in the questionnaires or pivotal study\n\nExclusion Criteria:\n\n* Physician in training (cardiology fellow or advanced imaging fellow)","ALL","18 Years",{"count":67,"type":68},50,"ESTIMATED","OBSERVATIONAL","Heart disease is the leading cause of death in the United States, and echocardiography (or \"echo\") is the most common way doctors look at the heart. Echo is safe, painless, and can detect major heart problems, including weak heart pumping and valve disease.\n\nValve disease, especially aortic stenosis (narrowing) and mitral regurgitation (leakage), is common in older adults but often goes undiagnosed. While echo is the main tool for finding valve problems, it takes time, requires expert training, and results can vary between readers.\n\nRecent advances in artificial intelligence (AI), especially deep learning (DL), have shown promise in automatically analyzing heart images. However, past research hasn't fully tackled key echo techniques-like color Doppler and spectral Doppler-that are crucial for measuring how blood moves through heart valves. AI tools also face challenges in being used in everyday medical practice because of workflow issues, lack of real-world testing, and concerns about how the algorithms make decisions.\n\nAt Columbia University Irving Medical Center, researchers have built a large database of heart tests over the last six years and developed AI programs to analyze echocardiograms. The current study will test whether providing AI analysis to cardiologists in real time during echo reading can make the process faster and more consistent.",[72,73,74,75,76,77],"Valve Disease, Aortic","Mitral Regurgitation (MR)","Aortic Stenosis","Valvular Heart Disease","Tricuspid Regurgitation (TR)","Aortic Regurgitation",[79,80,81,82,83,84,85],"artificial intelligence","deep learning","valvular heart disease","echocardiography","cardiovascular disease","mitral regurgitation","aortic stenosis","2026-04-14",{"date":88,"type":89},"2026-04-16","ACTUAL",{"date":91,"type":68},"2026-04-15",{"date":93,"type":68},"2028-10-01",{"name":5,"class":6},1]