AID-OMIE - Artificial Intelligence in Detection of Occlusive Myocardial Infarction in Emergency Medicine

NCT06767709 | Not Yet Recruiting

• 1 other identifier: 01-2025
• Study Type: observational
• Target: 200
• Locations: 0 countries
• Sites: N/A

Brief Summary

Study Objective and Hypothesis The study hypothesizes that artificial intelligence (AI)-assisted interpretation of the 12-lead electrocardiogram (ECG) can improve the care of patients resuscitated after out-of-hospital cardiac arrest (OHCA) by enabling faster and more accurate detection of occlusion myocardial infarction (OMI). This enhanced diagnostic approach could reduce the time required for revascularization, improve patient outcomes, and decrease unnecessary activations of cardiac catheterization laboratories. The primary objective of the study is to assess the effectiveness of an AI-powered ECG model in identifying acute OMI in OHCA patients whose post-return of spontaneous circulation (ROSC) ECG does not show ST-elevation. Methods This is a retrospective observational study involving OHCA patients in Bolzano, Italy, who meet the following inclusion criteria: Aged 18 years or older. Achieved ROSC after cardiac arrest. Underwent coronary angiography (CAG) within seven days post-OHCA. Prehospital post-ROSC ECG and CAG reports available. Exclusion criteria include in-hospital cardiac arrest (IHCA), traumatic cardiac arrest, cardiac arrest from a non-cardiac cause, and poor-quality or corrupted ECG images. Post-ROSC ECGs will be analyzed using the PMcardio App, an AI tool for ECG interpretation. The data will be fully anonymized before storage. Coronary angiography charts will be reviewed for the presence of atherosclerotic lesions, the degree of arterial narrowing, and Thrombolysis in Myocardial Infarction (TIMI) flow, which assesses blood flow in coronary arteries. Study Outcomes The primary outcome is the sensitivity and specificity of the AI-assisted ECG in detecting OMI in patients whose post-ROSC ECG does not show ST-elevation. Secondary outcomes include the frequency of OMI in OHCA patients without ST-elevation and the ability of the AI model to rule out OMI accurately in these cases.

Conditions

Cardiac Arrest, Out-Of-Hospital; Cardiac Arrest Due to Underlying Cardiac Condition

Keywords

Cardiac arrest; OHCA; Occlusion myocardial infarction; OMI; Artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Sensitivity and specificity of detecting OMI from the post-ROSC ECG with AI-assisted ECG interpretation in patients following OHCA with ROSC, where the post-ROSC ECG does not show ST-elevation.

  Sensitivity and specificity of detecting occlusion myocardial infarction (OMI) from the electrocardiogram (ECG) taken after return of spontaneous circulation (ROSC) using artificial intelligence (AI)-assisted ECG interpretation in patients resuscitated from out-of-hospital cardiac arrest (OHCA) with ROSC, where the post-ROSC ECG does not display ST-segment elevation.

  Within 7 days after OHCA

Secondary Outcomes (2)

• Frequency of OMI post-OHCA without ST-elevation in the post-ROSC ECG

  Within 7 days after OHCA

• Sensitivity and specificity of excluding OMI with AI-assisted ECG interpretation in patients following OHCA with ROSC, where the post-ROSC ECG does not show ST-elevation.

  Within 7 days from OHCA

Study Arms (1)

Patients after Out-of-Hospital Cardiac Arrest (OHCA) with ROSC in the Province of Bolzano, Italy

Patients after Out-of-Hospital Cardiac Arrest (OHCA) with Return of Spontaneous Circulation (ROSC) in the Province of Bolzano, Italy

Eligibility Criteria

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

Study Population

Patients who suffered OHCA from presumed cardiac cause and sustained ROSC.

You may qualify if:

• OHCA from with ROSC in the Province of Bolzano, Italy
• Coronary angiography (CAG) within 7 days post-OHCA
• Age \> 18 years
• Available prehospital post-ROSC ECG
• Available CAG report

You may not qualify if:

• In-Hospital Cardiac Arrest (IHCA)
• Age \< 18 years
• Traumatic cardiac arrest
• Cardiac arrest from a clear non-cardiac cause
• Corrupted ECG images
• Poor ECG digitalization quality

Sponsors & Collaborators

• Institute of Mountain Emergency Medicine: lead

MeSH Terms

Conditions

Out-of-Hospital Cardiac Arrest; Heart Arrest

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Central Study Contacts

Simon Rauch, MD, PhD

CONTACT

+393404967398; simon.rauch@eurac.edu

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Senior Researcher

Study Record Dates

• First Submitted: January 5, 2025
• First Posted: January 10, 2025
• Study Start: September 1, 2025
• Primary Completion (Estimated): May 30, 2026
• Study Completion (Estimated): May 31, 2026
• Last Updated: August 8, 2025

Record last verified: 2025-08

Data Sharing

• IPD Sharing: Will not share