[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100629847":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":10,"centralContacts":24,"locations":30,"responsibleParty":58,"collaborators":10,"id":60,"slug":61,"hasResults":62,"nctId":63,"briefTitle":64,"officialTitle":65,"acronym":66,"eligibilityCriteria":67,"healthyVolunteers":68,"sex":69,"minAge":70,"maxAge":10,"enrollmentInfo":71,"targetDuration":10,"studyType":74,"phases":10,"briefSummary":75,"conditions":76,"keywords":78,"overallStatus":33,"whyStopped":10,"lastUpdateSubmitDate":84,"lastUpdatePostDateStruct":85,"startDateStruct":88,"completionDateStruct":90,"leadSponsor":92,"locationsCount":93},{"fullName":5,"class":6},"Idoven 1903 S.L.","INDUSTRY",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Aortic Stenosis patients",null,"Subjects with an Aortic Stenosis diagnosis confirmed by the physician following their routine practice (e.g. ESC Guidelines), including complete clinical assessment with echocardiogram or other complementary techniques.",[13],"Device: Willem AI ECG assessment",{"label":15,"type":10,"description":16,"interventionNames":17},"Non-Aortic Stenosis patients (Controls)","Subjects without Aortic Stenosis confirmed by the physician after thorough evaluation following their routine practice.",[13],[19],{"type":20,"name":21,"description":22,"armGroupLabels":23,"otherNames":10},"DEVICE","Willem AI ECG assessment","There is no study intervention. The Willem AI platform will assess all study electrocardiograms (ECGs) for the identification of aortic stenosis. Regardless of retrospective or prospective enrollment, Willem output will not be provided to the healthcare professional user for clinical evaluation, and therefore routine practice will not be impacted nor altered.",[9,15],[25],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},"Manuel Marina-Breysse, MD, PhD","CONTACT","+34669752391","clinical@idoven.ai",[31,46],{"facility":32,"status":33,"city":34,"state":10,"zip":10,"country":35,"countryCode":36,"cosmosGeoPoint":37,"geoPoint":42,"contacts":43},"Universitätsklinikum Bonn","RECRUITING","Bonn","Germany","DE",{"type":38,"coordinates":39},"Point",[40,41],7.09549,50.73438,{"lat":41,"lon":40},[44],{"name":45,"role":27,"phone":10,"phoneExt":10,"email":10},"Sebastian Zimmer, MD, PhD",{"facility":47,"status":48,"city":49,"state":10,"zip":10,"country":35,"countryCode":36,"cosmosGeoPoint":50,"geoPoint":54,"contacts":55},"Technical University of Munich","NOT_YET_RECRUITING","Munich",{"type":38,"coordinates":51},[52,53],11.57549,48.13743,{"lat":53,"lon":52},[56],{"name":57,"role":27,"phone":10,"phoneExt":10,"email":10},"Moritz von Scheidt, MD, PhD",{"type":59,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100629847","multicenter-study-for-the-validation-of-willem-ai-aortic-stenosis-early-diagnosis-with-ai-electrocardiogram-study-100629847",false,"NCT07479992","Multicenter Study for the Validation of Willem AI: Aortic StenoSis Early Diagnosis With AI-electrocardiogram Study","Multicenter Study for the Validation of Willem AI: Aortic StenoSis Early Diagnosis With AI-electrocardiogram (Willem AoS-SEDAI) Study","AoS-SEDAI","Inclusion Criteria:\n\n* Age ≥ 18 years;\n* All available 12-lead ECG with a 10 seconds minimum length on raw data digital format will be included\n* Available clinical data corresponding to each ECG to confirm patient demographics and Aortic Stenosis diagnosis\n* Available transthoracic echocardiogram (TTE) within +\u002F- 90 days of each ECG recording\n\nNo exclusion criteria are defined for this study.",true,"ALL","18 Years",{"count":72,"type":73},5000,"ESTIMATED","OBSERVATIONAL","AoS-SEDAI study is an observational, multicenter, retrospective and prospective clinical study.\n\nThis study aims to assess Willem Artificial Intelligence (AI) ability to distinguish between aortic stenosis (AS) and non-AS patients from 12-lead electrocardiogram (ECG) data.",[77],"Aortic Stenosis",[79,80,81,82,83],"artificial intelligence","electrocardiogram","deep learning","cardiac disease","aortic stenosis","2026-05-08",{"date":86,"type":87},"2026-05-12","ACTUAL",{"date":89,"type":87},"2026-04-28",{"date":91,"type":73},"2026-07",{"name":5,"class":6},2]