Healthcare-associated ventriculitis and meningitis in a neuro-ICU: Incidence and risk factors selected by machine learning approach.

Journal: Journal of critical care
PMID: 29413730

Abstract

PURPOSE: To define the incidence of healthcare-associated ventriculitis and meningitis (HAVM) in the neuro-ICU and to identify HAVM risk factors using tree-based machine learning (ML) algorithms.

Authors

  • Ivan Savin
    Burdenko Neurosurgery Institute, 16 4th Tverskaya-Yamskaya Street, Moscow 125047, Russia.
  • Ksenia Ershova
    Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Building 3, Moscow 143026, Russia; Department of Anesthesiology, Keck School of Medicine, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, USA. Electronic address: ksenia.ershova@skolkovotech.ru.
  • Nataliya Kurdyumova
    Burdenko Neurosurgery Institute, 16 4th Tverskaya-Yamskaya Street, Moscow 125047, Russia.
  • Olga Ershova
    Burdenko Neurosurgery Institute, 16 4th Tverskaya-Yamskaya Street, Moscow 125047, Russia.
  • Oleg Khomenko
    Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Building 3, Moscow 143026, Russia.
  • Gleb Danilov
    Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.
  • Michael Shifrin
    Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.
  • Vladimir Zelman
    Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Building 3, Moscow 143026, Russia; Department of Anesthesiology, Keck School of Medicine, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, USA.

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