TRIACS-MBNCT07882849

AI-ECG Detection of Occlusion Myocardial Infarction at Emergency Department Triage (TRIACS)

StatusNot Yet Recruiting

PhaseNot specified

SponsorUniversity Medical Centre Maribor

Primary completionOct 19, 2027 (estimated)

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Record History

All 1 version: 1 with changes below.

Oct 12, 2026 Study First Submitted

Endpoints

Primary

Diagnostic accuracy of the AI-ECG model for angiographically confirmed occlusion myocardial infarction

Timeframe: From triage ECG to 7 and 30 days after index presentation

Secondary (2)

Comparative diagnostic accuracy versus formal STEMI criteria

Versus conventional ST-elevation millimetre criteria

Arms and interventions

Suspected acute coronary syndrome at ED triage

Consecutive adults with a digitally captured triage 12-lead ECG. No intervention assigned; AI analysis performed on routinely acquired ECGs with output withheld from clinicians.

Sites

1 site in 1 country

UKC MariborMaribor, Slovenia

About this trial

Chest pain is among the most common reasons people attend an emergency department, and the electrocardiogram (ECG) recorded at triage is the first test used to decide who needs urgent treatment for a blocked coronary artery. Recognising the ECG patterns that indicate an acutely blocked artery is difficult. Many such patterns do not produce the classic ST-segment elevation, and identifying them reliably requires a level of ECG expertise that is not always available at the point of triage - particularly at night and among clinicians who are not cardiologists. Artificial intelligence (AI) models that read the 12-lead ECG have been shown in several retrospective studies, mainly from Western Europe and the United States, to identify acute coronary occlusion more sensitively than conventional interpretation. These models are now in clinical use in a number of health systems. Their performance has not been assessed in a prospectively enrolled, unselected Slovenian emergency department population, and diagnostic accuracy commonly declines when a model is applied outside the setting in which it was developed. TRIACS is a prospective, single-centre, observational external validation study in the Emergency Department of University Medical Centre Maribor. All consecutive adults presenting with symptoms suggestive of acute coronary syndrome who have a 12-lead ECG recorded at triage as part of routine care will be enrolled. Each triage ECG is analysed by the AI model. The model's output is withheld from all treating clinicians and plays no part in patient care; every patient receives standard guideline-directed management. The main aim is to measure how accurately the AI model identifies angiographically confirmed occlusion myocardial infarction in this population, and to compare its accuracy with the triage decision actually made by the clinical team. The study is therefore designed to inform an adoption decision in either direction, rather than to demonstrate a predetermined conclusion.

Trial details

Enrollment: 1,000 participants (estimated)
Started: Oct 19, 2026
Study completion: Nov 19, 2027 (estimated)
Eligibility: 18 and older, all sexes, no healthy volunteers
Design: Observational
Oversight: No data monitoring committee
Conditions: Acute Coronary Syndrome, Chest Pain, Emergencies, Myocardial Infarction, Non-ST Elevated Myocardial Infarction, ST Elevation Myocardial Infarction, Acute Coronary Syndromes, Myocardial Infarction (MI) +2 more
Collaborators: 3fs Nordic SI, d.o.o., University of Ljubljana
Official title: Prospective External Validation of an Artificial Intelligence Electrocardiogram Model for Detection of Occlusion Myocardial Infarction in Patients Presenting to Emergency Department Triage With Suspected Acute Coronary Syndrome: The TRIACS Study
First posted: Oct 20, 2026
Registry updated: Oct 20, 2026
Last verified: Oct 2026

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