Actively Recruiting

Age: 18Years +
All Genders
NCT06819618

Prediction of Heart-Failure with Machine Learning

Led by University Medical Center Goettingen · Updated on 2025-02-11

32

Participants Needed

1

Research Sites

60 weeks

Total Duration

On this page

AI-Summary

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.

CONDITIONS

Official Title

Prediction of Heart-Failure with Machine Learning

Who Can Participate

Age: 18Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Age over 17 years
  • Diagnosed with heart failure with reduced ejection fraction (LV-EF under 41%)
  • Hospitalized for decompensated heart failure with nTproBNP over 1000
  • Willing to participate in the study
  • Presence of at least one clinical sign: edema, pleural effusion, or ascites
Not Eligible

You will not qualify if you...

  • Life expectancy under 6 months due to non-cardiac conditions
  • Unable to use a smartwatch
  • Severe valvular heart lesions

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 1 location

1

University Medical Center Goettingen

Goettigen, Lower Saxony, Germany, 37075

Actively Recruiting

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Research Team

S

Soeren Sievers, Dr. med.

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

1

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