Machine Learning-Based Prediction of Chronic Shunt-Dependent Hydrocephalus After Spontaneous Subarachnoid Hemorrhage.

Journal: World neurosurgery
PMID: 39276974

Abstract

BACKGROUND: Chronic posthemorrhagic hydrocephalus often arises following spontaneous subarachnoid hemorrhage (SAH). Timely identification of patients predisposed to develop chronic shunt-dependent hydrocephalus may significantly enhance clinical outcomes.

Authors

  • Maria Gollwitzer
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria; Johannes Kepler University Linz, Linz, Austria.
  • Markus Steindl
    Johannes Kepler University Linz, Linz, Austria; RISC Software GmbH, Hagenberg, Austria.
  • Nico Stroh
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria; Johannes Kepler University Linz, Linz, Austria. Electronic address: nico.stroh@kepleruniklinikum.at.
  • Anna Hauser
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
  • Gracija Sardi
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
  • Tobias Rossmann
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria; Johannes Kepler University Linz, Linz, Austria.
  • Stefan Aspalter
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University, Linz , Austria.
  • Philip Rauch
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University, Linz , Austria.
  • Michael Sonnberger
    Institute of Neuroradiology, Kepler University Hospital Linz, Linz, Austria.
  • Andreas Gruber
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University, Linz , Austria.
  • Matthias Gmeiner
    Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University, Linz , Austria.

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