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AI-ECG for Predicting CMR-Defined Myocardial Injury in Acute Myocardial Infarction

NCT07751809 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 461

Last updated 2026-08-07

No results posted yet for this study

Summary

This retrospective, single-center external validation study evaluates whether two commercially approved artificial intelligence-enhanced electrocardiography (AI-ECG) algorithms (AiTiA LVSD and AiTiA MI; Medical AI Co., Ltd.), applied to a single pre-percutaneous coronary intervention (PCI) 12-lead ECG, predict cardiac magnetic resonance (CMR)-defined myocardial injury in patients with acute myocardial infarction (AMI). The primary endpoint is a large infarct (late gadolinium enhancement \>17.9% of left ventricular mass); secondary endpoints are CMR left ventricular ejection fraction (LVEF) ≤40% and microvascular obstruction (MVO).

Conditions

  • Acute Myocardial Infarction (AMI)

Sponsors & Collaborators

  • Medical AI

    collaborator INDUSTRY

  • Yonsei University

    lead OTHER

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-04-01
Primary Completion
2025-06-30
Completion
2025-06-30

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 NCT07751809 on ClinicalTrials.gov