RecruitingNCT06819618

Prediction of Heart-Failure with Machine Learning

Predicting Heart Failure Recovery by Wearables and Machine Learning

Sponsor

University Medical Center Goettingen

Enrollment

32 participants

Start Date

Apr 1, 2024

Study Type

OBSERVATIONAL

Conditions

Heart Failure Heart Failure With Reduced Ejection Fraction Heart Failure; With Decompensation Heart Failure, Congestive Heart Failure Acute

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

Min Age: 18 Years

Plain Language Summary

Simplified for easier understanding

This study uses machine learning (AI) to predict outcomes in patients hospitalized with worsening heart failure. Participants will wear a smartwatch to provide real-time health data that feeds into a predictive model. **You may be eligible if...** - You are over 17 years old - You have heart failure with reduced pumping function (ejection fraction below 41%) - You have been hospitalized for worsening (decompensated) heart failure, with high levels of a heart stress marker (NT-proBNP over 1000) and at least one physical sign such as leg swelling, fluid around the lungs, or fluid in the abdomen **You may NOT be eligible if...** - Your life expectancy is less than 6 months due to a non-heart condition - You are unable to use a smartwatch - You have severe heart valve disease Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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