Stratification of Early Arrhythmic Risk in Patients Admitted for Acute Coronary Syndrome: The Role of the Machine Learning-Derived "PRAISE Score".

Journal: Clinical cardiology
PMID: 39699030

Abstract

BACKGROUND: The PRAISE (PRedicting with Artificial Intelligence riSk aftEr acute coronary syndrome) score is a machine learning-based model for predicting 1-year adverse cardiovascular or bleeding events in patients with acute coronary syndrome (ACS). Its role in predicting arrhythmic complications in ACS remains unknown.

Authors

  • Luca Cumitini
    Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy.
  • Ailia Giubertoni
    Division of Cardiology, Maggiore della Carità Hospital, Novara, Italy.
  • Lidia Rossi
    Division of Cardiology, Maggiore della Carità Hospital, Novara, Italy.
  • Domenico D'Amario
    Department of Cardiovascular and Thoracic Sciences, Catholic University of the Sacred Heart, Fondazione Policlinico Universitario A. Gemelli, 8, 00168 Largo A. Gemelli, Italy. domenico.damario@gmail.com.
  • Leonardo Grisafi
    University of Eastern Piedmont, Maggiore della Carità Hospital, Novara, Italy.
  • Paola Abbiati
    Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy.
  • Fabrizio D'Ascenzo
    Division of Cardiology, Cardiovascular and Thoracic Department, Città della Salute e della Scienza, Turin, Italy; Cardiology, Department of Medical Sciences, University of Turin, Turin, Italy. Electronic address: fabrizio.dascenzo@gmail.com.
  • Gaetano Maria De Ferrari
    Coronary Care Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
  • Giuseppe Patti
    Department of Thoracic, Heart and Vascular Diseases, Maggiore Della Carità Hospital, Corso Mazzini 18, 28100 Novara, Italy.

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