Prediction of Heart-Failure with Machine Learning
Recruiting · NCT06819618 · Observational (researchers observe without assigning treatment) · Lead sponsor: University Medical Center Goettingen
View the official record on ClinicalTrials.gov →Interventions studied
What this trial is about
In this monocentric observational study the research question is to what extent data collected via Apple Watch can predict the heart failure status of decompensated HF patients. For this purpose, physiological data from the Apple Watch (such as single-lead electrocardiogram, SpO2, respiratory rate, step count, nighttime temperature, etc.) will be extracted and used as predictor variables to forecast outcomes like risk of decompensation and rehospitalization within the follow-up period. Since this is a data-driven study, additional data collected as part of guideline-compliant treatment will also be included.
Who can take part
Inclusion criteria
- age over 17
- HFrEF with LV-EF under 41
- hospitalized for decompensated heart failure with a) nTproBNP over 1000 AND b) willing to participate AND c) at least one out of three clinical signs (edema, pleural effusion, ascites)
Exclusion criteria
- life expectancy under 6 months due to non-cardiac conditions
- inability to use smartwatch
- severe valvular lesions
Where it is running
1 location listed.
- University Medical Center Goettingen - Goettigen, Lower Saxony, Germany