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ME-TIME: Machine Learning Enabled Time Series Analysis in Medicine

Sponsor
HagaZiekenhuis (Other)
Overall Status
Enrolling by invitation
CT.gov ID
NCT05802563
Collaborator
Delft University of Technology (Other)
200
Enrollment
1
Location
15.3
Anticipated Duration (Months)
13.1
Patients Per Site Per Month

Study Details

Study Description

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.

Condition or Disease Intervention/Treatment Phase
  • Device: fitness tracker

Study Design

Study Type:
Observational
Anticipated Enrollment :
200 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Pattern Recognition in Heart Rate Variability Using Fitness Trackers in Cardiovascular Disease
Actual Study Start Date :
May 24, 2022
Anticipated Primary Completion Date :
Sep 1, 2023
Anticipated Study Completion Date :
Sep 1, 2023

Arms and Interventions

Arm Intervention/Treatment
Heart Failure

Study participants with systolic heart failure (Left ventricular ejection fraction < 35%) without documented atrial fibrillation

Device: fitness tracker
Study subjects will wear a Fitbit fitness tracker
Other Names:
  • Fitbit Charge 5, Fitbit Inspire 2

    		•
    Atrial Fibrillation

    Study participants with documented atrial fibrillation without heart failure

    Device: fitness tracker
    Study subjects will wear a Fitbit fitness tracker
    Other Names:
  • Fitbit Charge 5, Fitbit Inspire 2

    		•
    Reference

    Individuals without cardiovascular disease

    Device: fitness tracker
    Study subjects will wear a Fitbit fitness tracker
    Other Names:
  • Fitbit Charge 5, Fitbit Inspire 2

    		•

    Outcome Measures

    Primary Outcome Measures

    1. Cardiovascular disease detection with an AI algorithm [Three months]

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

    Secondary Outcome Measures

    1. Detection of absence of cardiovascular disease [Three months]

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years to 85 Years
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    Yes
    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

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 HagaZiekenhuis Den Haag Zuid-Holland Netherlands 2545 AA

    Sponsors and Collaborators

    • HagaZiekenhuis
    • Delft University of Technology

    Investigators

    None specified.

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Ivo van der Bilt, Principal Investigator, HagaZiekenhuis
    ClinicalTrials.gov Identifier:
    NCT05802563
    Other Study ID Numbers:
    • metime
    First Posted:
    Apr 6, 2023
    Last Update Posted:
    Apr 7, 2023
    Last Verified:
    Apr 1, 2023
    Individual Participant Data (IPD) Sharing Statement:
    Yes
    Plan to Share IPD:
    Yes
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Keywords provided by Ivo van der Bilt, Principal Investigator, HagaZiekenhuis
    cardiovascular disease
    Artificial intelligence
    machine learning
    Additional relevant MeSH terms:
    Atrial Fibrillation
    Heart Failure, Systolic

    Study Results

    No Results Posted as of Apr 7, 2023