Rationale and design of the artificial intelligence scalable solution for acute myocardial infarction (ASSIST) study.

Journal: Journal of electrocardiology
PMID:

Abstract

BACKGROUND: Acute coronary syndrome (ACS), specifically ST-segment elevation myocardial infarction is a major cause of morbidity and mortality throughout Europe. Diagnosis in the acute setting is mainly based on clinical symptoms and physician's interpretation of an electrocardiogram (ECG), which may be subject to errors. ST-segment elevation is the leading criteria to activate urgent reperfusion therapy, but a clear ST-elevation pattern might not be present in patients with coronary occlusion and ST-segment elevation might be seen in patients with normal coronary arteries.

Authors

  • Tomás Domingo-Gardeta
    Department of Cardiology, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; Centro de Investigación Biomédica en Red. Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain; Facultad de Medicina, Universidad Complutense, 28040 Madrid, Spain.
  • José M Montero-Cabezas
    Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
  • Alfonso Jurado-Román
    Cardiology Department, La Paz University Hospital, Fundación de Investigación Hospital La Paz, IdiPaz Madrid, Spain.
  • Manel Sabaté
    Centro de Investigación Biomédica en Red. Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain; Institut Clínic Cardiovascular, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
  • Jaime Aboal
    Servicio de Cardiología, Hospital Universitario Josep Trueta, Girona, Spain.
  • Adrian Baranchuk
    Division of Cardiology, Queen's University, Kingston, Ontario, Canada.
  • Xavier Carrillo
    Hospital Germans Trias i Pujol, Badalona, Spain.
  • Sebastián García-Zamora
    Department of Cardiology, Sanatorio Delta, Rosario, Argentina.
  • Hélder Dores
    Luz Hospital Lisbon, Lisbon, Portugal; NOVA Medical School, Lisbon, Portugal; CHRC, NOVA Medical School, Lisbon, Portugal.
  • Viktor van der Valk
    Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
  • Roderick W C Scherptong
    Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
  • Joan F Andrés-Cordón
    Hospital Germans Trias i Pujol, Badalona, Spain.
  • Pablo Vidal
    Institut Clínic Cardiovascular, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain.
  • Daniel Moreno-Martínez
    Hospital Germans Trias i Pujol, Badalona, Spain; Research group on innovation, health economics and digital transformation, Germans Trias i Pujol Research Institute.
  • Raquel Toribio-Fernández
    Idoven Research, Madrid, Spain.
  • José María Lillo-Castellano
    IDOVEN Research, Madrid, Spain; Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.
  • Roberto Cruz
    Idoven Research, Madrid, Spain.
  • François De Guio
    Idoven Research, Madrid, Spain.
  • Manuel Marina-Breysse
    Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain; IDOVEN Research, Madrid, Spain; Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.
  • Manuel Martínez-Sellés
    Servicio de Cardiología, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Spain; Facultad de Medicina, Universidad Complutense, Madrid, Spain; Facultad de Ciencias Biomédicas y de la Salud, Universidad Europea, Madrid, Spain. Electronic address: mmselles@secardiologia.es.