A machine-learning based analysis for the recognition of progressive central hypovolemia.

Journal: Physiological measurement
Published Date: Aug 21, 2017

Abstract

OBJECTIVE: Traditional patient monitoring during surgery includes heart rate (HR), blood pressure (BP) and peripheral oxygen saturation. However, their use as predictors for central hypovolemia is limited, which may lead to cerebral hypoperfusion. The aim of this study was to develop a monitoring model that can indicate a decrease in central blood volume (CBV) at an early stage.

Authors

  • Frank C Bennis
    Department of Biomedical Engineering, Maastricht University, PO Box 616, 6200 MD, Maastricht, Netherlands. MHeNS School for Mental Health and Neuroscience, Maastricht University, PO Box 616, 6200 MD, Maastricht, Netherlands.
  • Björn Jp van der Ster
  • Johannes J van Lieshout
    Department of Internal Medicine, University of Amsterdam, Amsterdam, Netherlands.
  • Peter Andriessen
    4Department of NeonatologyMáxima Medical Center5504DBVeldhovenThe Netherlands.
  • Tammo Delhaas

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