Actively Recruiting
Evaluating the Accuracy and Practical Utility of AI-Enhanced 12-Lead ECG
Led by Toho University · Updated on 2026-01-07
350
Participants Needed
1
Research Sites
155 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Atrial fibrillation (AF) is a major cause of heart failure and ischemic stroke, making early detection and intervention critically important. However, timely ECG recording during paroxysmal episodes is often difficult, leading to delayed diagnosis. Recently, an AI-enhanced 12-lead ECG equipped with a "hidden AF risk estimation" function has been introduced. This technology analyzes sinus rhythm ECGs and stratifies the likelihood of prior AF into four risk categories. Although this novel approach may facilitate earlier AF detection and optimize the timing of therapeutic intervention, its clinical accuracy and real-world utility remain insufficiently validated. Therefore, this multicenter study aims to evaluate the diagnostic performance and clinical usefulness of AI-based AF risk assessment and to clarify its association with subsequent AF incidence and patient outcomes.
CONDITIONS
Official Title
Evaluating the Accuracy and Practical Utility of AI-Enhanced 12-Lead ECG
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Age 18 years or older
- Patients with atrial fibrillation or atrial tachycardia who maintain or can confirm sinus rhythm during ECG recording
You will not qualify if you...
- Age under 18 years
- History of long-standing persistent or permanent atrial fibrillation
- Frequent premature beats preventing sinus rhythm ECG acquisition
- No clinical indication to suspect atrial fibrillation
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Toho University
Ōta-ku, Tokyo, Japan, 143-8540
Actively Recruiting
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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