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

NCT ID: NCT05689970

Last Updated: 2024-03-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

420 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-07-25

Study Completion Date

2024-07-24

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.

Conditions

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STEMI - ST Elevation Myocardial Infarction

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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STE patients

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).

AI platform to detect ST elevation in ECG

Intervention Type DIAGNOSTIC_TEST

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.

STEMI patients

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.

AI platform to detect ST elevation in ECG

Intervention Type DIAGNOSTIC_TEST

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.

Interventions

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AI platform to detect ST elevation in ECG

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.

Intervention Type DIAGNOSTIC_TEST

Other Intervention Names

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Willem platform Idoven AI

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).
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Hospital General Universitario Gregorio Marañon

OTHER

Sponsor Role collaborator

Spanish Society of Cardiology

OTHER

Sponsor Role collaborator

Idoven 1903 S.L.

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Manuel Martínez-Sellés, MD

Role: PRINCIPAL_INVESTIGATOR

Hospital Universitario Gregorio Marañón

Locations

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Hospital Universitario de Canarias

San Cristóbal de La Laguna, Santa Cruz De Tenerife, Spain

Site Status

Hospital de Basurto

Bilbao, Vizcaya, Spain

Site Status

Hospital Vall D' Hebron

Barcelona, , Spain

Site Status

Idoven

Madrid, , Spain

Site Status

Servicio Cardiología Hospital Universitario Gregorio Marañón

Madrid, , Spain

Site Status

Hospital Clínico San Carlos

Madrid, , Spain

Site Status

Hospital Clínico Universitario de Valladolid

Valladolid, , Spain

Site Status

Countries

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Spain

References

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Martinez-Selles M, Bueno H, Sacristan A, Estevez A, Ortiz J, Gallego L, Fernandez-Aviles F. Chest pain in the emergency department: incidence, clinical characteristics and risk stratification. Rev Esp Cardiol. 2008 Sep;61(9):953-9. English, Spanish.

Reference Type BACKGROUND
PMID: 18775237 (View on PubMed)

Lillo-Castellano JM, Gonzalez-Ferrer JJ, Marina-Breysse M, Martinez-Ferrer JB, Perez-Alvarez L, Alzueta J, Martinez JG, Rodriguez A, Rodriguez-Perez JC, Anguera I, Vinolas X, Garcia-Alberola A, Quintanilla JG, Alfonso-Almazan JM, Garcia J, Borrego L, Canadas-Godoy V, Perez-Castellano N, Perez-Villacastin J, Jimenez-Diaz J, Jalife J, Filgueiras-Rama D. Personalized monitoring of electrical remodelling during atrial fibrillation progression via remote transmissions from implantable devices. Europace. 2020 May 1;22(5):704-715. doi: 10.1093/europace/euz331.

Reference Type BACKGROUND
PMID: 31840163 (View on PubMed)

Quartieri F, Marina-Breysse M, Pollastrelli A, Paini I, Lizcano C, Lillo-Castellano JM, Grammatico A. Artificial intelligence augments detection accuracy of cardiac insertable cardiac monitors: Results from a pilot prospective observational study. Cardiovasc Digit Health J. 2022 Aug 4;3(5):201-211. doi: 10.1016/j.cvdhj.2022.07.071. eCollection 2022 Oct.

Reference Type BACKGROUND
PMID: 36310681 (View on PubMed)

Study Documents

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Document Type: Study Protocol

View Document

Other Identifiers

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350/21

Identifier Type: -

Identifier Source: org_study_id

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