Prediction of Heart-Failure with Machine Learning

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity Medical Center Goettingen

About this trial

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.

Eligibility criteria

Qualifiers

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)

Disqualifiers

life expectancy under 6 months due to non-cardiac conditions

inability to use smartwatch

severe valvular lesions

Trial design

Treatments tested in this trial

  • Monitoring with Apple Watch

Treatment groups

32 Participants
are divided into 1 treatment group

Locations

1

Map coordinates are unavailable for these locations. Locations are shown below instead.

University Medical Center GoettingenRecruiting37075, Goettigen, Lower SaxonyGermanyGermany