Artificial Intelligence Based Timing, Infarct Size and Outcomes in Acute Coronary Occlusion Myocardial Infarction

NCT06910436 | Recruiting

• 1 other identifier: ANOMI
• Study Type: observational
• Target: 1,500
• Locations: 1 country
• Sites: 1

Brief Summary

The present study is practice-driven and merely observational and prospective. In clinical routine, patients who suffer from suspected ACS and do not show ST elevation in the ECG, different timing proposals in the guidelines and logistically driven differences lead to considerably variable timings in invasive coronary anatomy assessments. This handling may lead to larger infarct sizes when OMI is overseen. Therefore, the present study aims to observe a) whether an AI model is capable of correctly identify OMI in eligible patients and b) if in these patients troponin peak levels vary depending on the elapsed time between OMI diagnosis and coronary intervention. As the model has not been established yet clinically and in the guidelines, it is safe to assume the usual pathway from first medical contact to specialist's attention is undertaken. When a patient presents in an emergency department or places an emergency call, the physicians assess the situation as usal and as stated in the current guidelines1. If no STEMI is confirmed, the NSTE-ACS protocol is started. The patients who are ruled out for ACS are excluded from the final analysis (screening). In this case, the AI model is tested on their ECG in order to assess whether there are false positives. The patients which are in the ACS "rule-in" trail and undergo final coronary angiography will naturally be divided in patients which were classified as OMI and as non-OMI by the AI model. Furthermore, they will present a different "Time from OMI diagnosis to PCI) and variable troponin peak levels. By leveraging this natural variability, a practical distinction and multiple analyses can be done:

1. 1.The feasibility of AI-powered ECG interpretation in the care of patients with suspected ACS and without clear ST-elevation infarction
2. 2.The accuracy of AI-powered ECG interpretation in detecting OMI compared to the classical STEMI criteria
3. 3.How infarct size correlates with different ECG readings by AI and (hypothesis generating) if changing the clinical practice could lead to a benefit in patients with suspected OMI.

Conditions

Coronary Arterial Disease (CAD); Acute Coronary Syndrome (ACS) Undergoing Percutaneous Coronary Intervention (PCI)

Keywords

Artificial Intelligence; ECG; AI; NSTE-ACS; ACS; Acute Coronary Syndrome; Reperfusion times; PCI; Percutaneous Coronary Intervention

Outcome Measures

Primary Outcomes (2)

• Cardiovascular Mortality

  Cardiovascular Mortality

  12 months

• Infarct Size

  Infarct size measured by transthoracic echocardiogram or cardiac magnetic resonance imaging

  12 months

Other Outcomes (1)

• Performance of AI-based OMI detection

  Periprocedural (at the time of coronary angiography)

Study Arms (1)

NSTE-ACS

Patients with Non ST-Elevation myocardial infarction

Diagnostic Test: Coronary Angiogram

Interventions

Coronary Angiogram DIAGNOSTIC_TEST

Diagnostic/therapeutic procedure to reopen an occluded coronary artery by inflating a balloon and inserting a stent

NSTE-ACS

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients presenting with chest pain and deemed as Non-ST Elevation Myocardial Infarction by the specialist, whether in the emergency medicine setting or in-hospital

You may qualify if:

• Age \> 18 yrs
• Working diagnosis of Non- ST Elevation Acute Coronary Syndrome after the assessment by specialist

You may not qualify if:

• ST-Elevation Myocardial infarction
• Age \< 18 yrs
• Major sustained ventricular arrhythmias
• Corrupted ECG images
• Poor digitalisation quality of the ECG

Sponsors & Collaborators

• Azienda Ospedaliera di Bolzano: lead

Study Sites (1)

Azienda Sanitaria di Bolzano

Bolzano, BZ, 39100, Italy

RECRUITING

MeSH Terms

Conditions

Acute Coronary Syndrome

Interventions

Coronary Angiography

Condition Hierarchy (Ancestors)

Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Vascular Diseases

Intervention Hierarchy (Ancestors)

Cardiac Imaging Techniques; Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis; Angiography; Radiography; Diagnostic Techniques, Cardiovascular; Heart Function Tests

Central Study Contacts

Matthias Unterhuber, MD, Associate Prof.

CONTACT

+39 471 43 9950; matthias.unterhuber@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 12 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assoc. Prof. Dr.med. Dr. Med.univ. Matthias Unterhuber

Study Record Dates

• First Submitted: March 28, 2025
• First Posted: April 4, 2025
• Study Start: April 1, 2024
• Primary Completion (Estimated): July 31, 2026
• Study Completion (Estimated): July 31, 2026
• Last Updated: April 21, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)