The revised Cerebral Recovery Index improves predictions of neurological outcome after cardiac arrest.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
PMID: 30390546

Abstract

OBJECTIVE: Analysis of the electroencephalogram (EEG) background pattern helps predicting neurological outcome of comatose patients after cardiac arrest (CA). Visual analysis may not extract all discriminative information. We present predictive values of the revised Cerebral Recovery Index (rCRI), based on continuous extraction and combination of a large set of evolving quantitative EEG (qEEG) features and machine learning techniques.

Authors

  • Sunil B Nagaraj
    1Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.2Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA.3Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA.4Department of Electronics, Informatics and Bioengineering, Politecnico di Milano, Milan, Italy.
  • Marleen C Tjepkema-Cloostermans
    Department of Clinical Neurophysiology and Neurology, Medisch Spectrum Twente, Enschede, The Netherlands. Electronic address: m.tjepkema-cloostermans@mst.nl.
  • Barry J Ruijter
    Clinical Neurophysiology Group, University of Twente, Enschede, Netherlands.
  • Jeannette Hofmeijer
    Clinical Neurophysiology Group, University of Twente, Enschede, Netherlands; Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands.
  • Michel J A M van Putten
    Department of Clinical Neurophysiology, MIRA-Institute for Biomedical Technology and Technical Medicine, University of Twente & Medisch Spectrum Twente, Enschede, The Netherlands. m.j.a.m.vanputten@utwente.nl.

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