Wearables and Artificial Intelligence in Advanced Heart Failure Care (NCT07051356) | Clinical Trial Compass
Not Yet RecruitingNot Applicable
Wearables and Artificial Intelligence in Advanced Heart Failure Care
Netherlands200 participantsStarted 2025-07
Plain-language summary
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.
The main questions it aims to answer are:
* Can AI-driven analysis of wearable data detect physiological or behavioral changes associated with impending hospital admissions?
* Does wearable-based remote monitoring influence daily exercise duration in patients with advanced heart failure.
* Is wearable-based remote monitoring usable and acceptable for patients with advanced heart failure in a real-world setting?
Participants 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.
Who can participate
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Inclusion Criteria:
* \>18 years.
* Diagnosis of advanced heart failure, including at least one of the following major criteria.
* LVAD implanted
* Included on the waiting list for Heart transplant
* Meeting the European Society of CArdiology criteria for advanced HF:
* Severe and persistent symptoms of heart failure \[NYHA class III or IV\].
* Severe cardiac dysfunction: according to ESC guidelines definition
* ≥ 1 unplanned visit or hospitalization in the last 12 months requiring IV treatment.
* Have access to a mobile phone or tablet with an operating system iSO 15 or Android 9 (or posterior versions of these systems).
Exclusion Criteria:
* Impossibility to provide inform consent.
* Impossibility to self-report data due to physical or mental disability.
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
Algorithm Performance Metrics
Timeframe: From enrollment to the end of the monitoring period at 1 year.