MedTrace Logo

Prediction of Heart-Failure with Machine Learning

NCT06819618 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 32

Last updated 2025-02-11

No results posted yet for this study

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.

Conditions

  • Heart Failure with Reduced Ejection Fraction
  • Heart Failure
  • Heart Failure，Congestive
  • Heart Failure Acute
  • Heart Failure; with Decompensation

Interventions

OTHER

Monitoring with Apple Watch

Patients will receive Apple Watch for Monitoring of Biosignals throughout the hospital stay

Sponsors & Collaborators

  • University Medical Center Goettingen

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-04-01
Primary Completion
2025-05-31
Completion
2025-05-31

Countries

  • Germany

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06819618 on ClinicalTrials.gov