title: Comparison of the predictive performance of the BIG, TRISS, and PS09 score in an adult trauma population derived from multiple international trauma registries.
abstract: BACKGROUND
  The BIG score (Admission base deficit (B), International normalized ratio (I), and Glasgow Coma Scale (G)) has been shown to predict mortality on admission in pediatric trauma patients. The objective of this study was to assess its performance in predicting mortality in an adult trauma population, and to compare it with the existing Trauma and Injury Severity Score (TRISS) and probability of survival (PS09) score.
  
  
  METHODS
  A retrospective analysis using data collected between 2005 and 2010 from seven trauma centers and registries in Europe and the United States of America was performed. We compared the BIG score with TRISS and PS09 scores in a population of blunt and penetrating trauma patients. We then assessed the discrimination ability of all scores via receiver operating characteristic (ROC) curves and compared the expected mortality rate (precision) of all scores with the observed mortality rate.
  
  
  RESULTS
  In total, 12,206 datasets were retrieved to validate the BIG score. The mean ISS was 15 ± 11, and the mean 30-day mortality rate was 4.8%. With an AUROC of 0.892 (95% confidence interval (CI): 0.879 to 0.906), the BIG score performed well in an adult population. TRISS had an area under ROC (AUROC) of 0.922 (0.913 to 0.932) and the PS09 score of 0.825 (0.915 to 0.934). On a penetrating-trauma population, the BIG score had an AUROC result of 0.920 (0.898 to 0.942) compared with the PS09 score (AUROC of 0.921; 0.902 to 0.939) and TRISS (0.929; 0.912 to 0.947).
  
  
  CONCLUSIONS
  The BIG score is a good predictor of mortality in the adult trauma population. It performed well compared with TRISS and the PS09 score, although it has significantly less discriminative ability. In a penetrating-trauma population, the BIG score performed better than in a population with blunt trauma. The BIG score has the advantage of being available shortly after admission and may be used to predict clinical prognosis or as a research tool to risk stratify trauma patients into clinical trials.
authors.forename: Thomas
authors.initials: T
authors.lastname: Brockamp
authors.forename: Marc
authors.initials: M
authors.lastname: Maegele
authors.forename: Christine
authors.initials: C
authors.lastname: Gaarder
authors.forename: J Carel
authors.initials: JC
authors.lastname: Goslings
authors.forename: Mitchell J
authors.initials: MJ
authors.lastname: Cohen
authors.forename: Rolf
authors.initials: R
authors.lastname: Lefering
authors.forename: Pieter
authors.initials: P
authors.lastname: Joosse
authors.forename: Paal A
authors.initials: PA
authors.lastname: Naess
authors.forename: Nils O
authors.initials: NO
authors.lastname: Skaga
authors.forename: Tahnee
authors.initials: T
authors.lastname: Groat
authors.forename: Simon
authors.initials: S
authors.lastname: Eaglestone
authors.forename: Matthew A
authors.initials: MA
authors.lastname: Borgman
authors.forename: Philip C
authors.initials: PC
authors.lastname: Spinella
authors.forename: Martin A
authors.initials: MA
authors.lastname: Schreiber
authors.forename: Karim
authors.initials: K
authors.lastname: Brohi
mesh_terms: D000328:Adult; D005060:Europe / Q000453:epidemiology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008889:Military Personnel; D011336:Probability; D012372:ROC Curve; D012042:Registries; D012189:Retrospective Studies; D015599:Trauma Severity Indices; D014481:United States / Q000453:epidemiology; D014949:Wounds, Nonpenetrating / Q000175:diagnosis* / Q000401:mortality*; D014950:Wounds, Penetrating / Q000175:diagnosis* / Q000401:mortality*