Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning.

Journal: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
PMID: 30508072

Abstract

AIMS: Electrical storm (ES) is a serious arrhythmic syndrome that is characterized by recurrent episodes of ventricular arrhythmias. Electrical storm is associated with increased mortality and morbidity despite the use of implantable cardioverter-defibrillators (ICDs). Predicting ES could be essential; however, models for predicting this event have never been developed. The goal of this study was to construct and validate machine learning models to predict ES based on daily ICD remote monitoring summaries.

Authors

  • Saeed Shakibfar
    Department of Drug Design and Pharmacology, Pharmacovigilance Research Center, University of Copenhagen, Copenhagen, Denmark.
  • Oswin Krause
    Department of Computer Science, University of Copenhagen, Universitetsparken 5, Copenhagen 2100, Denmark.
  • Casper Lund-Andersen
    Department of Cardiology, The Heart Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
  • Alfonso Aranda
    Medtronic, Medtronic Bakken Research Center, Maastricht, The Netherlands.
  • Jonas Moll
    Department of Computer Science, University of Copenhagen, Universitetsparken 5, Copenhagen 2100, Denmark.
  • Tariq Osman Andersen
    Department of Computer Science, University of Copenhagen, Universitetsparken 5, Copenhagen 2100, Denmark.
  • Jesper Hastrup Svendsen
    Department of Cardiology, The Heart Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
  • Helen Høgh Petersen
    Department of Cardiology, The Heart Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
  • Christian Igel
    Department of Computer Science, University of Copenhagen, Copenhagen Ø DK-2100, Denmark.

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