A Predictive Model for Massive Transfusion in Combat Casualty Patients

Abstract

Massive transfusion (MT) is associated with increased morbidity and mortality in severely injured patients. Early and aggressive use of blood products in these patients may correct coagulopathy, control bleeding, and improve outcomes. However, rapid identification of patients at risk for MT has been difficult. We postulated that evaluation of clinical variables routinely assessed upon admission would allow identification of these patients for earlier, more effective intervention. Methods: A retrospective cohort

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2008
Accession Number
ADA480419

Entities

People

  • Charles E Wade
  • Daniel F. Mclaughlin
  • E. D. Cox
  • Jeremy G. Perkins
  • John B Holcomb
  • Josè Salinas
  • Sarah E. Niles

Organizations

  • United States Army Institute of Surgical Research

Tags

DTIC Thesaurus Topics

  • Blood
  • Blood Transfusions
  • Cardiovascular Physiological Phenomena
  • Casualties
  • Combat Support
  • Combat Support Hospitals
  • Data Science
  • Data Sets
  • Databases
  • Health Services
  • Heart Rate
  • Hospitals
  • Information Science
  • Patient Care
  • Predictive Modeling
  • Therapy
  • Wounds And Injuries

Fields of Study

  • Medicine

Readers

  • Software Engineering
  • Trauma or Military Medicine