|

Prediction of Heart-Failure with Machine Learning

RECRUITINGSponsored by University Medical Center Goettingen
Actively Recruiting
SponsorUniversity Medical Center Goettingen
Started2024-04-01
Est. completion2025-05-31
Eligibility
Age18 Years+
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT06819618

Summary

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

Age: 18 Years+Healthy volunteers accepted
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

Conditions6

Heart DiseaseHeart FailureHeart Failure AcuteHeart Failure With Reduced Ejection FractionHeart Failure, CongestiveHeart Failure; With Decompensation

Browse More Trials

Heart Disease trials

Trial data from ClinicalTrials.gov. Trial status and eligibility can change — verify directly with the study contact or on ClinicalTrials.gov.

This site does not provide medical advice. Always consult your doctor before considering enrollment in a clinical trial. Learn more on our About page.