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Evaluating the Accuracy and Practical Utility of AI-Enhanced 12-Lead ECG

NCT07316231 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 350

Last updated 2026-01-07

No results posted yet for this study

Summary

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

  • AI-enhanced 12-lead ECG

Sponsors & Collaborators

  • Toho University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
99 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-09-11
Primary Completion
2027-12-31
Completion
2028-08-31

Countries

  • Japan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07316231 on ClinicalTrials.gov