Wearables and Artificial Intelligence in Advanced Heart Failure Care
ConditionAdvanced Heart Failure
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUMC Utrecht
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
>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
Disqualifiers
Impossibility to provide inform consent.
Impossibility to self-report data due to physical or mental disability.
Trial population
Patients who are under care at the UMC Utrecht due to advanced heart failure, are on the wating list for heart transplant or have received an LVAD as treatment (either as bridge to transplant or as destination therapy).
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
Primary outcomes
1
Algorithm Performance Metrics
Algorithm's performance to detect imminent admission in patients with advanced HF will be measured by means of the following parameters: Accuracy, sensitivity, specificity, negative predictive value, positive predictive value, area under the ROC curve.
Time frame
From enrollment to the end of the monitoring period at 1 year.Secondary outcomes
1
Change in daily exercise duration
Daily exercise duration will be measured using the wrist worn-device. Exercise duration will be measured in minutes of activity per day and step count per day.
Time frame
From baseline to the end of the monitoring period at 1 year.2
Perceived usability
Perceived usability will be assessed by means of The System Usability Scale (SUS). SUS is a widely used, validated tool for assessing the usability of a system, product, or technology. SUS is a 10-item questionnaire with statements about the system being evaluated. Each item is rated on a 5-point Likert scale (from Strongly Disagree \[1\] to Strongly Agree \[5\]). The single score ranges from 0 to 100 where higher scores indicate better usability.
Time frame
At 1-yearSponsors and contacts
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Source ClinicalTrials.gov
This trial is not recruiting at the moment. You can still explore other options: