Atrial Fibrillation Risk Estimation With Single-lead Handheld Electrocardiograms

Enrolling by invitation · Not applicable

Conditions studied: Atrial Fibrillation (AF)

In brief

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 facts

Study ID
NCT07468123
Run by
Massachusetts General Hospital
People needed
200
Starts
2025-07-30
Expected to finish
2027-12-31
Last updated by the study team
2026-03-12

Who can join

Age: 18 and older, up to 90. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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