About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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
Disqualifiers
In-Hospital Cardiac Arrest (IHCA)
Age < 18 years
Traumatic cardiac arrest
Cardiac arrest from a clear non-cardiac cause
Trial population
Patients who suffered OHCA from presumed cardiac cause and sustained ROSC.
Trial design
Case-only
Retrospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
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.
Secondary outcomes
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.
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.
Sensitivity and specificity of ruling out occlusion myocardial infarction (OMI) using artificial intelligence (AI)-assisted electrocardiogram (ECG) interpretation in patients resuscitated from out-of-hospital cardiac arrest (OHCA) who achieved return of spontaneous circulation (ROSC), where the post-ROSC ECG does not display ST-segment elevation.
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