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9 Variables abstracted from the trauma registry included age, sex, mechanism of injury, initial ED GCS score, initial systolic blood pressure (SBP), heart rate, and respiratory rate, revised trauma score (physiological scoring system based on initial GCS, SBP, and respiratory rate),10 blood alcohol level, initial hematocrit, AIS score and injury severity score (ISS) (anatomical scoring system),11 ED disposition, hospital length of stay, in-hospital mortality, and hospital selleck screening library disposition. Variables abstracted from the TBI database included admission GCS score (GCS score at the time of admission), initial platelet count and international normalized ratio (INR), initial CT characteristics and prognostic score (Rotterdam CT score), 12 in-hospital neurosurgical interventions, and GOS-E AZD6738 mw score at six months. Outcomes Our primary outcome measure was a dichotomized GOS-E score at six months (8 [fully recovered] versus 1�C7 [not fully recovered]). The GOS-E is the most commonly used measure of global functional performance after TBI and has been recommended as the criterion standard outcome measure for TBI studies.13,14 It uses an 8-category score that is typically dichotomized between 8 and 1�C7 for mild TBI to facilitate interpretation.15 It has excellent interrater reliability and content validity.8 We also conducted a sensitivity analysis adjusting the dichotomization at GOS-E 1�C6 versus GOS-E 7 and 8. The secondary outcome measure was hospital MASP1 length of stay (days in the hospital). Outcomes were collected independent of the knowledge of ED disposition. Analysis We conducted data formatting and recoding of variables ducted using STATA 11.0 statistical software (STATA Corp, College Station, TX). The study population was characterized using descriptive statistics. Non-normal interval data were reported with medians and interquartile ranges, and proportions were presented with 95% confidence intervals (CIs). We analyzed categorical data with chi-square test or Fischer��s exact test in cases of small cell size. Continuous data were analyzed with Student��s t-test if normally distributed. We used Wilcoxon rank-sum test for nonparametric data or ordinal data. Since inherent differences likely existed between low-risk patients admitted to the ICU and those admitted to the floor we created boxplots to analyze the distribution of key independent variables (age, initial systolic blood pressure, AIS head and neck score, and Rotterdam CT score) by hospital admission location (floor versus ICU). Boxplots were also created to analyze outcome measures. Bivariate analyses on these variables and GOS-E score were also done to evaluate which variables may have influenced the GOS-E score. We then fit a logistic regression model with these variables using the dichotomized GOS-E score (8 versus