Machine Learning Enabled Time Series Analysis in Medicine (ME-TIME)

HagaZiekenhuis

Status: Invitation-only

Conditions: Atrial Fibrillation; Heart Failure, Systolic

Treatments: Device: fitness tracker

Study type: Observational

Funder types: Other

Identifiers

NCT05802563

metime

Details and patient eligibility

About

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.

Enrollment: 200 estimated patients

Sex: All

Ages: 18 to 85 years old

Volunteers: Accepts Healthy Volunteers

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

Trial design

200 participants in 3 patient groups

Heart Failure

Description:

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

Treatment:

Device: fitness tracker

Atrial Fibrillation

Description:

Study participants with documented atrial fibrillation without heart failure

Treatment:

Device: fitness tracker

Reference

Description:

Individuals without cardiovascular disease

Treatment:

Device: fitness tracker