Abstract 336: The Novel and Useful Scoring System to Predit Massive Transfusion for Trauma Patients: Traumatic Bleeding Severity Score (TBSS)

Abstract

Background: There is no clear criterion to activate massive transfusion (MT) for trauma patients. Several studies showed that Trauma Associated Severe Hemorrhage (TASH) score and Assessment of Blood Consumption (ABC) Score were high accuracy in predicting the necessity of MT for trauma patients. However, some study showed that the accuracy of these scoring systems for elderly patients was not perfect. In japan, since the population is aging and the number of elderly trauma patient increases, these scoring systems are not useful so much. The aim of this study was to create new scoring system and predict the necessity of MT for trauma patients using it. Methods: In the first analysis, new scoring system was created. We enrolled 119 severe trauma patients admitted to our center between January 2008 and December 2010. MT predictors were found by statistical methods from clinical and laboratory variables in the Primary Survey. Each MT predictor was converted into the simple score based on each odds ratio in multivariate logistic regression analysis. TBSS was defined as the total of each score. In the second analysis, the accuracy of TBSS was tested. 114 patients admitted between January 2010 and March 2012 were examined. Receiver operating characteristic curve analysis were performed to compare the accuracy between TBSS and conventional scoring systems (TASH Score and ABC Score). Results: In the first analysis, five preditors of MT were identified: age (> 60 year-old = 6pts), systolic blood pressure (< 110 mmHg = 4pts, < 100 mmHg = 8pts, < 90 mmHg = 12pts), positive focused assessment with sonography for trauma (FAST) ( [the number of regions with positive FAST] × 3pts), severity of pelvic fracture (stable fracture = 3pts, incomplete unstable fracture = 6pts, complete unstable fracture = 9pts), and lactate (> 2.5 mmol/L = 4pts, > 5.0 mmol/L = 8pts, > 7.5 mmol/L = 12pts). In the second analysis, TBSS excellently predicted MT (area under the curve (AUC) =0.985, p<0.01). The AUC of TBSS was higher than that of TASH Score (AUC=0.887) and ABC Score (AUC=0.809) (both Bonferoni adjusted p<0.05). Conclusion: TBSS based on the Primary Survey is high accuracy in predicting the necessity of MT. TBSS provide more useful information to predict MT compared with TASH Score and ABC Score.