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Functional And STructural Assesment of the Heart by Artificial Intelligence-enabled Electrocardiogram for the Management of Atrial Fibrillation

NCT07486739 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1724

Last updated 2026-03-23

No results posted yet for this study

Summary

The objective of this study is to evaluate whether an AI-ECG based screening strategy for detecting cardiac functional and structural abnormalities preserves clinical effectiveness and safety, compared with a conventional strategy of routine echocardiography in patients with AF, thereby demonstrating the non-inferiority of AI-ECG guided care.

Conditions

  • Atrial Fibrillation (AF)

Interventions

DIAGNOSTIC_TEST

Artificial intelligence-enabled electrocardiography

An artificial intelligence algorithm applied to standard 12-lead electrocardiography designed to predict cardiac structural or functional abnormalities. This tool guides the decision to perform or withhold downstream echocardiography.

DIAGNOSTIC_TEST

Transthoracic Echocardiography-Guided Assessment

Standard Transthoracic Echocardiography used to assess cardiac structure and function, serving as the reference standard for guiding clinical management in this study arm.

Sponsors & Collaborators

  • Medical AI

    collaborator INDUSTRY

  • Seoul National University Hospital

    lead OTHER

Principal Investigators

  • Eue-Keun Choi, M.D. Ph.D. · Seoul National University Hospital

Study Design

Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-05-31
Primary Completion
2030-12-31
Completion
2030-12-31

Countries

  • South Korea

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 NCT07486739 on ClinicalTrials.gov