AI-enhanced 12-lead ECG to reveal hidden atrial fibrillation risk
Official title: Toho Multicenter Registry for Evaluating the Accuracy and Practical Utility of AI-Enhanced 12-Lead ECG in Monitoring Atrial Fibrillation
Run by Toho University · NCT07316231 · Data updated 2026-11-12
This project will test whether an AI-enhanced 12-lead ECG can detect hidden or future atrial fibrillation risk in adults who are in sinus rhythm.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years to 99 Years |
| Sex | All |
| Enrollment | 350 (estimated) |
| Sponsor | Toho University Academic / other |
| Locations | 1 site (Ōta-ku, Tokyo) |
| Status | Recruiting |
| Started | September 11, 2025 |
| Main results expected | December 31, 2027 |
| Study ends | August 31, 2028 |
| Registry record updated | January 7, 2026 |
| Trial ID | NCT07316231 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (≥18) with paroxysmal or suspected AF/AT who are in sinus rhythm at the time of ECG recording and have a clinical reason to suspect AF are the ideal candidates.
✕Probably not a fit
Patients with long-standing persistent or permanent AF, frequent premature beats that prevent acquiring a sinus-rhythm ECG, or no clinical indication to suspect AF are unlikely to benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study applies an AI algorithm to standard 12-lead ECGs that classifies sinus-rhythm traces into four risk categories for prior AF. Adults with AF/AT who are in or can be confirmed in sinus rhythm at the time of ECG will be enrolled and followed for subsequent AF events and clinical outcomes. The study will compare AI risk categories with later documented AF episodes, routine clinical data, and outcomes such as stroke or heart failure to measure diagnostic accuracy and clinical usefulness. The aim is to clarify how well the tool predicts incident or previously undetected AF and whether it can inform monitoring and treatment timing.
Why it matters
Potential benefit: If accurate, the tool could help identify patients who need closer monitoring or earlier treatment to reduce the risk of stroke and heart failure.
How similar studies have gone: Previous studies using AI on sinus-rhythm ECGs have shown promising ability to predict occult or future AF, but broader real-world validation is still limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria 1. Age ≥18 years 2. Patients with atrial fibrillation or atrial tachycardia (AF/AT) in whom sinus rhythm is maintained or can be confirmed at the time of ECG recording Exclusion Criteria 1. Age \<18 years 2. History of long-standing persistent or permanent atrial fibrillation 3. Frequent premature beats preventing acquisition of a sinus rhythm ECG 4. Patients with no clinical indication to suspect atrial fibrillation
Where it's running
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Toho University
Ōta-ku, Tokyo, Japan Recruiting
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.