ST-segment Elevation Not Associated With Acute Cardiac Necrosis (LESTONNAC)

Study Overview
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Brief Summary
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Patients with chest pain and persistent ST segment elevation (STE) may not have acute coronary occlusions or serum troponin curves suggestive of acute necrosis. Our objective is the validation and cost-effectiveness analysis of a diagnostic model assisted by artificial intelligence (AI). Our hypothesis is that an AI analysis of the surface electrocardiogram allows a better distinction of patients with STE due to acute myocardial ischemia, from those with another etiology. This is a prospective multicenter study with two groups of patients with STE: I) coronary arteries without significant lesions and without serum troponin curve suggestive of acute necrosis, II) myocardial infarction with acute coronary occlusion. A manual centralized electrocardiographic analysis and another by AI algorithms will be performed.

Detailed Description
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This is a prospective multicenter study promoted by the Ischemic Heart Disease and Acute Cardiovascular Care Section of the Spanish Society of Cardiology. Following institutional ethical approval, the surface ECG prior to the activation of the Infarction Code, and the ECGs before and after (up to a maximum of 20) the Infarction Code along with other clinical data will be collected across the different enrolled hospitals. Sites will securely transfer the data to a centralized repository for processing. Willem AI platform will automatically analyze the ECGs in parallel to an experienced observer. The results of the study will provide new information for the improvement in the stratification of patients with ST segment elevation.

Official Title
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LESTONNAC Study: Observed ST Elevation Does Not Require Acute Cardiac Necrosis

Conditions
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STEMI - ST Elevation Myocardial Infarction

Intervention / Treatment
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* Diagnostic Test: AI platform to detect ST elevation in ECG


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age≥18 years. Chest pain or symptoms suggestive of myocardial ischemia. STE at point J in the12-lead electrocardiogram prior to activation of the infarction code in two contiguous leads ≥0.1 mV, in V2 and V3 ≥0.2 mV. Signature of informed consent. Exclusion Criteria: Left bundle branch block. Acute cardiac necrosis in the absence of significant epicardial coronary artery stenosis >70% (vasospasm, takotsubo stress cardiomyopathy, myocarditis, coronary artery dissection, acute myocardial infarction without obstructive coronary lesions - MINOCA). STE≤0.1 mV with pathologic Q wave suggestive of previous chronic infarction. Severe anemia (hemoglobin <8.0 g/dl).

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| STE patients<br>Patients with ST segment elevation (STE) and coronary arteries without significant lesions and without a serum troponin curve suggestive of acute necrosis (group without acute myocardial necrosis). | Diagnostic Test: AI platform to detect ST elevation in ECG<br>* A clinical decision support software as a medical device that detects whether a patient has ST elevation due to acute myocardial ischemia or due to another etiology based upon the input of one or more ECGs and other clinical data obtained at the point-of-care.<br>* Other names: Idoven AI;|
| STEMI patients<br>Patients with ST segment elevation with acute occlusion of at least one epicardial coronary artery and TIMI flow 0 or I (group with acute myocardial necrosis of ischemic origin), that meet the definition of myocardial infarction (STEMI) with an acute cardiac necrosis curve verified by measurement of troponin I or troponin T. | Diagnostic Test: AI platform to detect ST elevation in ECG<br>* A clinical decision support software as a medical device that detects whether a patient has ST elevation due to acute myocardial ischemia or due to another etiology based upon the input of one or more ECGs and other clinical data obtained at the point-of-care.<br>* Other names: Idoven AI;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Clinical validation of a screening model assisted by AI | The detection performance of acute myocardial ischemia will be evaluated for the AI platform in comparison to standard manual analysis. | 6 months after the last enrolled patient | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Cost-effectiveness analysis of a screening model assisted by AI | The benefits of the screening model assisted by the AI platform will be evaluated using a hybrid decision tree/ Markov model. | 1 year after the last enrolled patient | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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ST segment elevation, Artificial intelligence, Electrocardiogram, Acute myocardial infarction