title: Hemoperitoneum semiquantitative analysis on admission of blunt trauma patients improves the prediction of massive transfusion.
abstract: BACKGROUND
  The purpose of this study was to define whether the semiquantitative analysis of hemoperitoneum increases the accuracy of early prediction of massive transfusion (MT).
  
  
  METHODS
  A retrospective review of severe trauma patients consecutively admitted to our trauma intensive care unit between January 2005 and December 2009 was conducted. Patients diagnosed with blunt abdominal trauma who had a computed tomography scan on admission were included. The hemoperitoneum size was defined using the Federle score on computed tomography as large, moderate, or minimal/none. The association between MT (≥10 U of packed red blood cells in the first 24 h) and moderate and large sizes of hemoperitoneum was assessed using a multiple logistic model.
  
  
  RESULTS
  Of the 381 patients meeting the inclusion criteria, 270 (71%) were male; the mean age was 35.5 ± 18.2 years and mean injury severity score was 23.4 ± 17. Ninety-seven (26%) had large hemoperitoneum, 107 (28%) had moderate hemoperitoneum, and 177 (46%) had minimal/no hemoperitoneum. Eighty-three patients (22%) required MT. The positive predictive value for MT of a large hemoperitoneum was 41%, 23% for a moderate hemoperitoneum, and 10% for minimal/no hemoperitoneum (P < .001). The corresponding values for hypotensive patients were 61%, 32%, and 25%, respectively (P < .001). In the multivariate analysis model, only the large size of hemoperitoneum was significantly associated with MT (OR 6.4, 95% CI 2.9-14, P < .001, r(2) = 0.47).
  
  
  CONCLUSIONS
  The assessment of the size of hemoperitoneum on admission substantially improves the prediction of MT in trauma patients and should be used to trigger and guide initial haemostatic resuscitation.
authors.affiliation: Department of Anesthesiology and Critical Care, Lapeyronie University Hospital, Montpellier, F-34295 Cedex 5, France. j-charbit@chu-montpellier.fr
authors.forename: Jonathan
authors.initials: J
authors.lastname: Charbit
authors.forename: Martin
authors.initials: M
authors.lastname: Mahul
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Roustan
authors.forename: Pascal
authors.initials: P
authors.lastname: Latry
authors.forename: Ingrid
authors.initials: I
authors.lastname: Millet
authors.forename: Patrice
authors.initials: P
authors.lastname: Taourel
authors.forename: Xavier
authors.initials: X
authors.lastname: Capdevila
mesh_terms: D018806:APACHE; D000328:Adult; D000704:Analysis of Variance; D001803:Blood Transfusion / Q000706:statistics & numerical data*; D016009:Chi-Square Distribution; D005260:Female; D006465:Hemoperitoneum / Q000000981:diagnostic imaging* / Q000209:etiology* / Q000628:therapy*; D006801:Humans; D015601:Injury Severity Score; D007362:Intensive Care Units; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed; D014949:Wounds, Nonpenetrating / Q000150:complications* / Q000000981:diagnostic imaging*