[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100618586":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":10,"centralContacts":24,"locations":30,"responsibleParty":100,"collaborators":10,"id":102,"slug":103,"hasResults":104,"nctId":105,"briefTitle":106,"officialTitle":106,"acronym":107,"eligibilityCriteria":108,"healthyVolunteers":109,"sex":110,"minAge":111,"maxAge":10,"enrollmentInfo":112,"targetDuration":10,"studyType":115,"phases":10,"briefSummary":116,"conditions":117,"keywords":119,"overallStatus":33,"whyStopped":10,"lastUpdateSubmitDate":125,"lastUpdatePostDateStruct":126,"startDateStruct":129,"completionDateStruct":131,"leadSponsor":133,"locationsCount":134},{"fullName":5,"class":6},"Idoven 1903 S.L.","INDUSTRY",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"High-risk cardiac patients",null,"High-risk cardiac patients undergoing routine care electrocardiogram (ECG) for assessment of arrhythmias or cardiac diseases",[13],"Device: Willem AI ECG assessment",{"label":15,"type":10,"description":16,"interventionNames":17},"Controls","In case of any cardiac disease diagnosed to the high-risk cardiac patient cohort, controls will be any enrolled patient with no confirmed diagnosis of such cardiac disease",[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 ECGs for the identification of cardiac patterns, arrhythmias, and\u002For cardiac diseases. 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.",[15,9],[25],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},"Manuel Marina-Breysse, MD, PhD","CONTACT","+34669752391","clinical@idoven.ai",[31,48,64,79,88],{"facility":32,"status":33,"city":34,"state":35,"zip":36,"country":37,"countryCode":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Vanderbilt University Medical Center","RECRUITING","Nashville","Tennessee","37232","United States","US",{"type":40,"coordinates":41},"Point",[42,43],-86.78444,36.16589,{"lat":43,"lon":42},[46],{"name":47,"role":27,"phone":10,"phoneExt":10,"email":10},"Evan Brittain, MD, MSCI",{"facility":49,"status":33,"city":50,"state":51,"zip":52,"country":53,"countryCode":54,"cosmosGeoPoint":55,"geoPoint":59,"contacts":60},"CardioHeredia","Guayaquil","Guayas","090101 - 090158","Ecuador","EC",{"type":40,"coordinates":56},[57,58],-79.88621,-2.19616,{"lat":58,"lon":57},[61],{"name":62,"role":27,"phone":10,"phoneExt":10,"email":63},"Cinthia Madrid","cmadrid@cardioheredia.com",{"facility":65,"status":66,"city":67,"state":10,"zip":68,"country":69,"countryCode":70,"cosmosGeoPoint":71,"geoPoint":75,"contacts":76},"La Paz University Hospital","NOT_YET_RECRUITING","Madrid","28046","Spain","ES",{"type":40,"coordinates":72},[73,74],-3.70256,40.4165,{"lat":74,"lon":73},[77],{"name":78,"role":27,"phone":10,"phoneExt":10,"email":10},"Teresa López, MD, PhD",{"facility":80,"status":33,"city":67,"state":10,"zip":81,"country":69,"countryCode":70,"cosmosGeoPoint":82,"geoPoint":84,"contacts":85},"Puerta de Hierro University Hospital","28222",{"type":40,"coordinates":83},[73,74],{"lat":74,"lon":73},[86],{"name":87,"role":27,"phone":10,"phoneExt":10,"email":10},"Pablo García Pavía, MD, PhD",{"facility":89,"status":66,"city":90,"state":10,"zip":91,"country":69,"countryCode":70,"cosmosGeoPoint":92,"geoPoint":96,"contacts":97},"Murcia University","Murcia","30100",{"type":40,"coordinates":93},[94,95],-1.13004,37.98704,{"lat":95,"lon":94},[98],{"name":99,"role":27,"phone":10,"phoneExt":10,"email":10},"Sergio Manzano Fernández, MD, PhD",{"type":101,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100618586","registry-study-for-the-evaluation-of-high-risk-cardiac-patients-by-willem-ai-based-ecg-platform-100618586",false,"NCT07333547","Registry Study for the Evaluation of High-risk Cardiac Patients by WILLEM AI-based ECG Platform","WILLEMRegistry","Inclusion Criteria:\n\n* EC\u002FIRB approval of ICF waiver prior to recruitment; otherwise, signed informed consent form by subject and investigator\n* Age \\> 18 years-old, with no upper limit\n* Subjects undergoing standard of care electrocardiogram (ECG) of any duration from any hardware device\n* All available, but at least one, legible ECG tracings in raw data format (e.g. DICOM, XML, EDF, JSON, HL7, SCP, WFDB, CSV, etc.)\n* Available subject clinical data associated with the ECG\n* For 12-lead ECGs, a minimum length of 10 seconds at a minimum sample frequency of 250 Hz\n* For ECGs from Holters, wearables, patches, insertable cardiac monitors, telemetries, etc., a minimum length of 30 seconds at a minimum sample frequency of 200 Hz with a lead I \u002F II or its MCL-DII lead approximation\n* For prospective eligibility only:\n* Signed informed consent form, unless previously waived by the EC\u002FIRB\n* Site technical viability for ECG and subject clinical data transfer (e.g. end-to-end integration following interoperability standards such as FHIR, HL7 or DICOM)\n\nExclusion Criteria:\n\n* Unavailable or suboptimal quality of the raw data from the ECG signal\n* Age \\\u003C 18 years-old",true,"ALL","18 Years",{"count":113,"type":114},200000,"ESTIMATED","OBSERVATIONAL","The WILLEM Registry is a large-scale, single-group, observational, registry study to collect continuous clinical evidence of Willem in real-world settings. Cardiovascular diseases are a major problem for public health and healthcare systems. Electrocardiograms (ECGs) are simple tests which increase diagnostic performance and early detection of cardiovascular diseases. However, its interpretation is complex, time consuming for cardiology experts, and entails high costs for healthcare systems. Willem allows AI-based automatic interpretation and its performance has been examined in previous clinical trials, but additional clinical evidence is needed for its integration in real-world clinical settings. This study will collect clinical evidence of Willem performance to detect cardiac abnormalities in ECGs from high-risk cardiac patients admitted to cardiovascular units.",[118],"High-risk Cardiac Patients",[120,121,122,123,124],"artificial intelligence","electrocardiogram","deep learning","cardiac disease","registry","2026-07-01",{"date":127,"type":128},"2026-07-02","ACTUAL",{"date":130,"type":128},"2026-02-03",{"date":132,"type":114},"2036-01",{"name":5,"class":6},5]