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Clinical Trials/NCT05802563
NCT05802563
Enrolling By Invitation
Not Applicable

Pattern Recognition in Heart Rate Variability Using Fitness Trackers in Cardiovascular Disease

HagaZiekenhuis1 site in 1 country200 target enrollmentMay 24, 2022

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Atrial Fibrillation
Sponsor
HagaZiekenhuis
Enrollment
200
Locations
1
Primary Endpoint
Cardiovascular disease detection with an AI algorithm
Status
Enrolling By Invitation
Last Updated
3 years ago

Overview

Brief Summary

The goal of this observational cohort study is to investigate the potential of fitness trackers in combination with machine learning algorithms to identify cardiovascular disease specific patterns.

Two hundred participants will be enrolled:

  1. 50 with heart failure
  2. 50 with atrial fibrillation
  3. 100 (healthy) individuals without the former two conditions

All participants are given a Fitbit device and monitored for three months. Researchers will compare differences in heart rate variability patterns between the groups and devise a machine learning algorithm to detect these patterns automatically.

Registry
clinicaltrials.gov
Start Date
May 24, 2022
End Date
September 1, 2023
Last Updated
3 years ago
Study Type
Observational
Sex
All

Investigators

Responsible Party
Principal Investigator
Principal Investigator

Ivo van der Bilt

Principal Investigator

HagaZiekenhuis

Eligibility Criteria

Inclusion Criteria

  • systolic heart failure (LVEF \< 35%)
  • Atrial fibrillation without heart failure
  • Individuals without cardiovascular disease

Exclusion Criteria

  • \> 85 years old
  • Recent pulmonary venous antrum isolation procedure (\<1 year)
  • (end stage) kidney failure
  • (end stage) liver failure
  • Study participants with known systemic active inflammatory disease
  • Study participants with impaired mental state
  • Inability to use a fitness tracker or mobile phone
  • Impaired cognition and inability to understand the study protocol

Outcomes

Primary Outcomes

Cardiovascular disease detection with an AI algorithm

Time Frame: Three months

adequate sensitivity/specificity in an algorithm to detect atrial fibrillation and heart failure

Secondary Outcomes

  • Detection of absence of cardiovascular disease(Three months)

Study Sites (1)

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