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

Abstract

BACKGROUNDThe 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.METHODSThis study compared systolic arterial pressure (SAP), heart rate (HR), stroke volume (SV), and CRI during whole blood resuscitation after 25% blood volume hemorrhage in baboons (n=12). The study was conducted at the Texas Biomedical Research Institute (San Antonio, TX)under an approved protocol by their Animal Care and Use Committee. Statistical analysis was performed using two repeated measures ANOVA and linear regression analysis.RESULTSSV, SAP, HR, and CRI were all sensitive to blood resuscitation. SV and SAP overshot baseline during resuscitation, but CRI did not. Target SAP for resuscitation is 80–90 mm Hg. The corresponding CRI value was approximately 0.25–0.30, which aligns with the transition from an unstable to a moderately compromised condition.CONCLUSIONSCRI can detect not only hemorrhage, but also blood resuscitation in baboons. CRI is equally effective as traditional vital signs for detecting blood resuscitation. The ease of tracking CRI makes it a potentially effective clinical tool for monitoring blood resuscitation.Support or Funding InformationFUNDING: US Army Medical Research and Materiel Command Combat Casualty Care Research Program