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Atrial Fibrillation Risk Estimation With Single-lead Handheld Electrocardiograms
Sponsor: Massachusetts General Hospital
Summary
The goal of this prospective, non-randomized pilot study is to learn whether predictions from a previously validated 12-lead ECG-based artificial intelligence (AI) algorithm (ECG-AI) identify people more likely to have undiagnosed atrial fibrillation (AF). The main questions it aims to answer are: Do people predicted to have high risk of AF using ECG-AI have a higher rate of new AF diagnosis using 1L ECG screening compared with people predicted to have a low risk? Do AI-based AF risk estimates from the 12-lead ECG correlate with AF risk estimates from the 1L ECG? Do people find 1L ECG screening for AF acceptable and useful? Participants will: Undergo screening with 1L ECG mailed to their home Complete a survey assessing attitudes toward 1L ECG screening Complete a 14-day patch monitor on 1 or 2 occasions depending on 1L ECG results
Key Details
Gender
All
Age Range
18 Years - 90 Years
Study Type
INTERVENTIONAL
Enrollment
200
Start Date
2025-07-30
Completion Date
2027-12-31
Last Updated
2026-03-12
Healthy Volunteers
Yes
Conditions
Interventions
1L ECG screening
Individuals will undergo 1L ECG screening using the AliveCor KardiaMobile 1L ECG device
Patch monitor
Individuals who are found to have evidence of AF on 1L ECG will undergo assessment with 14-day patch monitor at the time of initial screen. Otherwise all study participants will undergo 14-day patch monitor at the 1-year timepoint.
Locations (1)
Mass General Brigham
Boston, Massachusetts, United States