Increasing Cardiovascular Data Sampling Frequency and Referencing It to Baseline Improve Hemorrhage Detection.

Journal: Critical care explorations
Published Date: Oct 30, 2019

Abstract

UNLABELLED: We hypothesize that knowledge of a stable personalized baseline state and increased data sampling frequency would markedly improve the ability to detect progressive hypovolemia during hemorrhage earlier and with a lower false positive rate than when using less granular data.

Authors

  • Anthony Wertz
    Auton Lab, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA.
  • Andre L Holder
    Cardiopulmonary Research Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Mathieu Guillame-Bert
    Auton Lab, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA.
  • Gilles Clermont
    Cardiopulmonary Research Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Artur Dubrawski
    Auton Lab, School of Computer Science, Carnegie Mellon University Pittsburgh, PA, USA.
  • Michael R Pinsky
    Cardiopulmonary Research Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.

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