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AI-ECG for Predicting CMR-Defined Myocardial Injury in Acute Myocardial Infarction
Sponsor: Yonsei University
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).
Official title: Artificial Intelligence-Enhanced ECG for Predicting Cardiac Magnetic Resonance-Defined Myocardial Injury in Acute Myocardial Infarction: An External Validation Study
Key Details
Gender
All
Age Range
19 Years - Any
Study Type
OBSERVATIONAL
Enrollment
461
Start Date
2020-04-01
Completion Date
2025-06-30
Last Updated
2026-08-07
Healthy Volunteers
No
Conditions
Locations (1)
Yongin Severance Hospital, Yonsei University College of Medicine
Yongin-si, Gyeonggi-do, South Korea