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Prediction of Heart-Failure with Machine Learning

Study acronym: PRE-HF-ML
StatusRecruiting
PhaseNot specified
Started
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Record status
This record was last updated February 11, 2025 (before its estimated May 31, 2025 completion). Its status may not reflect the trial's current state.

Record History

  1. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
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.
Trial Details
NCT Number NCT06819618
Lead Sponsor University Medical Center Goettingen
Conditions Heart Failure with Reduced Ejection Fraction, Heart Failure, Heart Failure，Congestive, Heart Failure Acute, Heart Failure; with Decompensation
Enrollment 32 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov