Deriving Automated Device Metadata From Intracranial Pressure Waveforms: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury ICU Physiology Cohort Analysis.

Journal: Critical care explorations
PMID: 39016273

Abstract

IMPORTANCE: Treatment for intracranial pressure (ICP) has been increasingly informed by machine learning (ML)-derived ICP waveform characteristics. There are gaps, however, in understanding how ICP monitor type may bias waveform characteristics used for these predictive tools since differences between external ventricular drain (EVD) and intraparenchymal monitor (IPM)-derived waveforms have not been well accounted for.

Authors

  • Sophie E Ack
    Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
  • Rianne G F Dolmans
    Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
  • Brandon Foreman
    University of Cincinnati, OH, USA.
  • Geoffrey T Manley
    Weill Institute for Neurosciences, Brain and Spinal Injury Center, University of California, San Francisco (UCSF), San Francisco, California, United States of America.
  • Eric S Rosenthal
    Department of Neurology, Massachusetts General Hospital, Boston, MA.
  • Morteza Zabihi
    Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.

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