Effectiveness of the Compensatory Reserve Index in Monitoring Blood Resuscitation in Baboons

Abstract

The Compensatory Reserve Index (CRI) is a machine learning algorithm that detects the body's ability to compensate for blood loss by analysing changes in arterial waveforms. Previous studies have shown CRI to be more accurate than traditional vital signs in estimating an individual's risk of hemodynamic decompensation. However, the effectiveness of the CRI in monitoring volume resuscitation has not been evaluated. The purpose of this study is to assess the ability of CRI to detect volume resuscitation incomparison to traditional vital signs.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 01, 2016
Source ID
10.1096/fasebj.30.1_supplement.1215.1

Entities

People

  • Betty Nguyen
  • Carmen Hinojosa‐laborde
  • Greg Grudic
  • Jane Mulligan
  • Víctor A. Convertino

Organizations

  • United States Army Institute of Surgical Research
  • United States Army Medical Research and Development Command
  • University of California, Los Angeles

Tags

Fields of Study

  • Medicine

Readers

  • Cardiovascular Physiology
  • Sensor Fusion and Tracking Systems.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks