[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100596890":3},{"organization":4,"armGroups":7,"interventions":7,"overallOfficials":7,"centralContacts":7,"locations":8,"responsibleParty":19,"collaborators":23,"id":29,"slug":30,"hasResults":31,"nctId":32,"briefTitle":33,"officialTitle":34,"acronym":35,"eligibilityCriteria":36,"healthyVolunteers":31,"sex":37,"minAge":38,"maxAge":7,"enrollmentInfo":39,"targetDuration":7,"studyType":42,"phases":7,"briefSummary":43,"conditions":44,"keywords":46,"overallStatus":52,"whyStopped":7,"lastUpdateSubmitDate":53,"lastUpdatePostDateStruct":54,"startDateStruct":57,"completionDateStruct":59,"leadSponsor":61,"locationsCount":62},{"fullName":5,"class":6},"UMC Utrecht","OTHER",null,[9],{"facility":5,"status":7,"city":10,"state":7,"zip":7,"country":11,"countryCode":12,"cosmosGeoPoint":13,"geoPoint":18,"contacts":7},"Utrecht","Netherlands","NL",{"type":14,"coordinates":15},"Point",[16,17],5.12222,52.09083,{"lat":17,"lon":16},{"type":20,"investigatorFullName":21,"investigatorTitle":22,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"PRINCIPAL_INVESTIGATOR","Pim van der Harst","Professor. Head of the department of Cardiology, UMC Utrecht.",[24,26],{"name":25,"class":6},"Health Holland",{"name":27,"class":28},"Viduet Health","UNKNOWN","100596890","wearables-and-artificial-intelligence-in-advanced-heart-failure-care-100596890",false,"NCT07051356","Wearables and Artificial Intelligence in Advanced Heart Failure Care","Advancing Proactive Care in Advanced Heart Failure: Integrating AI and Continuous Remote Monitoring for Early Detection of Heart Failure Deterioration","WAI-HF","Inclusion Criteria:\n\n* \\>18 years.\n* Diagnosis of advanced heart failure, including at least one of the following major criteria.\n\n  * LVAD implanted\n  * Included on the waiting list for Heart transplant\n  * Meeting the European Society of CArdiology criteria for advanced HF:\n* Severe and persistent symptoms of heart failure \\[NYHA class III or IV\\].\n* Severe cardiac dysfunction: according to ESC guidelines definition\n* ≥ 1 unplanned visit or hospitalization in the last 12 months requiring IV treatment.\n* Have access to a mobile phone or tablet with an operating system iSO 15 or Android 9 (or posterior versions of these systems).\n\nExclusion Criteria:\n\n* Impossibility to provide inform consent.\n* Impossibility to self-report data due to physical or mental disability.","ALL","18 Years",{"count":40,"type":41},200,"ESTIMATED","OBSERVATIONAL","The goal of this observational study is to evaluate whether AI-based analyses of wearable sensor data can identify early signs of deterioration leading to hospitalization in patients with advanced heart failure.\n\nThe main questions it aims to answer are:\n\n* Can AI-driven analysis of wearable data detect physiological or behavioral changes associated with impending hospital admissions?\n* Does wearable-based remote monitoring influence daily exercise duration in patients with advanced heart failure.\n* Is wearable-based remote monitoring usable and acceptable for patients with advanced heart failure in a real-world setting?\n\nParticipants will wear a wrist-worn (Fitbit) device continuously for one year and will use an eHealth app to answer question about their symptoms. Participant's physical activity, heart rate, heart rate variability, respiratory rate, sleep quality, and symptomatic status will be monitored remotely.",[45],"Advanced Heart Failure",[47,48,49,50,51],"Advanced heart failure","Wearable device","Artificial intelligence","Remote monitoring","Left ventricular assist device","NOT_YET_RECRUITING","2025-06-25",{"date":55,"type":56},"2025-07-04","ACTUAL",{"date":58,"type":41},"2025-07",{"date":60,"type":41},"2027-08",{"name":5,"class":6},1]