Clinical gestalt and the prediction of @entity400 after XXXX .

@entity1 @entity400 @entity2286 @entity130
INTRODUCTION: Early recognition and treatment of @entity130 @entity1 requiring @entity400 ( @entity400 ) has been shown to reduce mortality. While many risk factors predicting @entity400 have been demonstrated, there is no universally accepted method or algorithm to identify these @entity1 . We hypothesised that even among experienced @entity130 surgeons, the clinical gestalt of identifying @entity1 who will require @entity400 is unreliable. METHODS: Transfusion and mortality outcomes after @entity130 were observed at 10 U.S. Level-1 @entity130 centres in @entity1 who survived >=  30 min after admission and received >=  1 unit of RBC within 6h of arrival. Subjects who received >=  10 units within 24h of admission were classified as @entity400 @entity1 . @entity130 surgeons were asked the clinical gestalt question "Is the @entity1 likely to be massively transfused?" 10 min after the @entity1 arrival. The performance of clinical gestalt to predict @entity400 was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. RESULTS: Of the 1245 @entity1 enrolled, 966 met inclusion criteria and 221 (23%) @entity1 received @entity400 . 415 (43%) were predicted to have a @entity400 and 551(57%) were predicted to not have @entity400 . @entity1 predicted to have @entity400 were younger, more often sustained penetrating @entity130 , had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p<0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. @entity2286 and NPV were 34.9% and 86.2% respectively. CONCLUSION: Data from this large multicenter trial demonstrates that predicting the need for @entity400 continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured @entity1 earlier.
