Compensatory reserve and pulse character: Enhanced potential to predict urgency for transfusion and other life-saving interventions after traumatic injury

Angelo V. Ciaraglia, Victor A. Convertino, Michael C. Johnson, Mark DeRosa, Susannah E. Nicholson, Brian J Eastridge

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Background: Field triage of trauma patients requires timely assessment of physiologic status to determine resuscitative needs. Vital signs and rudimentary assessments such as pulse character (PC) are used by first responders to guide decision making. The compensatory reserve measurement (CRM) has demonstrated utility as an easily interpretable method for assessing patient status. We hypothesized that the ability to identify injured patients requiring transfusion and other life-saving interventions (LSI) using a measurement of pulse character could be enhanced by the addition of the CRM. Methods: We performed a prospective observational study on 300 trauma patients admitted to a level I trauma center. CRM was recorded continuously after device placement on arrival. Patient demographics, field and trauma resuscitation unit vital signs, therapeutic interventions, and outcomes were collected. A field SBP <100 mmHg was utilized as a surrogate for abnormal PC as previously validated. A patient with a CRM threshold value of <60% was considered clinically compromised with a risk of onset of decompensated shock. Data were analyzed to assess the capacity of CRM and pulse character separately or in combination to predict LSI defined as need for transfusion, intubation, tube thoracostomy, or operative/ angiographic hemorrhage control. Results: An improvement in the predictive capability for LSI, transfusion, or a composite outcome was demonstrated by the combination of CRM and PC compared to either measure alone. Conclusions: Combining PC assessment with CRM has the potential to enhance the recognition of injured patients requiring life-saving intervention thus improving sensitivity of decision support for prehospital providers.

Original languageEnglish (US)
Pages (from-to)S130-S138
JournalTransfusion
Volume62
Issue numberS1
DOIs
StatePublished - Aug 2022

Keywords

  • life-saving intervention
  • machine learning
  • monitoring
  • prehospital
  • transfusion
  • triage
  • vital signs

ASJC Scopus subject areas

  • Hematology
  • Immunology and Allergy
  • Immunology

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