Skip to main content
OpenTrials
Recruiting

NCT Number: NCT06910436

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

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. The feasibility of AI-powered ECG interpretation in the care of patients with suspected ACS and without clear ST-elevation infarction 2. The accuracy of AI-powered ECG interpretation in detecting OMI compared to the classical STEMI criteria 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.

Recruiting

Interested in participating?

Request Info

Key information

Conditions

Coronary Arterial Disease (CAD) Acute Coronary Syndrome Acute Coronary Syndrome (ACS) Undergoing Percutaneous Coronary Intervention (PCI) Cardiovascular Diseases Heart Diseases Myocardial Ischemia Vascular Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Azienda Sanitaria di Bolzano

Bolzano, BZ, 39100, Italy

Location status: Recruiting

Location contact

Matthias MU Unterhuber, Assoc.Prof. Dr. Dr.

CONTACT

[email protected]

+39 0471 94 9950

About this study

The 12-lead electrocardiogram (ECG) is the most widely used initial diagnostic tool to guide the management of patients with suspected acute coronary syndrome (ACS). At present, ACS is divided into ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation acute coronary syndrome (NSTE-ACS), with different treatment protocols. However, some patients with NSTE-ACS have an acute coronary occlusion (OMI) and may benefit from immediate reperfusion by percutaneous coronary intervention (PCI), but are often treated late. ECG signs suggestive of OMI have been described, but their visual interpretation by experts is variable and suboptimal. Recent studies have shown that artificial intelligence (AI) models for ECG analysis can outperform clinicians in the detection of OMI, suggesting the potential use of AI to improve triage and timely access to PCI. The investigators therefore aim to use these models to analyze ECGs of Patients with NSTE-ACS and to check whether the model outputs OMI or not OMI. Based on that information, the investigators will analyze the time it had taken from admission to intervention (PCI), in order to correlate possible late reperfusions with infarct size of the ventricle. The hypothesis is that a occluded coronary artery will in fact produce a larger infarct size (scar) in the ventricle after longer occlusion times (=reperfusion time), therefore the patients will be dichotomized in early and late intervention patients and analyzed based on their infarct size and outcome, stratified by the OMI diagnosis made by the AI ECG algorithm.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

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

Exclusion criteria

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

Treatment and study plan

Coronary Angiogram

Diagnostic Test

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

Primary outcomes

  1. Cardiovascular Mortality

    Time frame: 12 months

    Cardiovascular Mortality

  2. Infarct Size

    Time frame: 12 months

    Infarct size measured by transthoracic echocardiogram or cardiac magnetic resonance imaging

Other outcomes

  1. Performance of AI-based OMI detection

    Time frame: Periprocedural (at the time of coronary angiography)

    The performance of the AI algorithm is determined in terms of sensititivity, specificity, negative and positive predictive value based on true negatives, true positives, false negatives and false positives to identify OMI according to the current definitions in literature.

Study contacts

Contact information is provided by the study sponsor or research team.

Matthias Unterhuber, MD, Associate Prof.

CONTACT

[email protected]

+39 471 43 9950

Sponsors and collaborators

Lead sponsor

Azienda Ospedaliera di Bolzano

Other

Registry information

Official study title

Artificial Intelligence Based Timing, Infarct Size and Outcomes in Acute Coronary Occlusion Myocardial Infarction Without ST Elevation

Acronym: ANOMI

Important dates

Study start
2024
Primary completion
2026
Study completion
2026
First posted
Apr 4, 2025
Registry last updated
May 26, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.