AID-OMIE - Artificial Intelligence in Detection of Occlus... | NCT06767709

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

NCT06767709

Sponsor

Institute of Mountain Emergency Medicine

Status

Not yet recruiting

Last Update Posted

Aug 8, 2025Actual

Enrollment

200Estimated

Phase

Not provided

Conditions

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

Interventions

Not provided

Countries

Not provided

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Aug 2025

Overall Recruitment Status or Expanded Access Status

Not yet recruiting

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Sep 1, 2025Estimated

Primary Completion Date

May 30, 2026Estimated

Completion Date

May 31, 2026Estimated

First Submitted Date

Jan 5, 2025

First Submission Date that Met QC Criteria

Jan 5, 2025

First Posted Date

Jan 10, 2025Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Aug 5, 2025

Last Update Posted Date

Aug 8, 2025Actual

Sponsor/Collaborators Module

Responsible Party, by Official Title

Simon Rauch, Senior Researcher, Institute of Mountain Emergency MedicinePrincipal Investigator

Lead Sponsor

Institute of Mountain Emergency MedicineOTHER

Collaborators

Not provided

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

FDAAA801 Violation

Not provided

Description Module

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.

Detailed Description

Methods

This is a retrospective observational study involving OHCA patients in Bolzano, Italy, who meet the following inclusion criteria:

OHCA from 2018-2025 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.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

200Estimated

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
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

Interventions

Not provided

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
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

Measure	Description	Time Frame
Frequency of OMI post-OHCA without ST-elevation in the post-ROSC ECG	Frequency of occlusion myocardial infarction (OMI) in patients resuscitated from out-of-hospital cardiac arrest (OHCA) who achieved return of spontaneous circulation (ROSC), where the electrocardiogram (ECG) recorded post-ROSC does not show ST-segment elevation.	Within 7 days after OHCA

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

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

Exclusion Criteria:

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

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

Not provided

Standard Ages

AdultOlder Adult

Study Population

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

Sampling Method

Non-Probability Sample

Name	Role	Phone	Extension	Email
Simon Rauch, MD, PhD	Contact	+393404967398		simon.rauch@eurac.edu

IPD Sharing Statement Module

Plan to Share IPD

Description

Not provided

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

Condition Browse Module

MeSH Terms

ID	Term
D058687	Out-of-Hospital Cardiac Arrest
D006323	Heart Arrest

Ancestor Terms

ID	Term
D006331	Heart Diseases
D002318	Cardiovascular Diseases

Browse Leaves

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Browse Branches

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