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Introduction: Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable., Methods: Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients 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 MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems., Results: Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, 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%. PPV and NPV were 34.9% and 86.2% respectively., Conclusion: Data from this large multicenter trial demonstrates that predicting the need for MT 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 patients earlier., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background: The trauma transfusion literature has yet to resolve which is more important for hemorrhaging patients, transfusing plasma and platelets along with red blood cells (RBCs) early in resuscitation or gradually balancing blood product ratios. In a previous report of PROMMTT results, we found (1) plasma and platelet:RBC ratios increased gradually during the 6 hours following admission, and (2) patients achieving ratios more than 1:2 (relative to ratios <1:2) had significantly decreased 6-hour to 24-hour mortality adjusting for baseline and time-varying covariates. To differentiate the association of in-hospital mortality with early plasma or platelet transfusion from that with delayed but gradually balanced ratios, we developed a separate analytic approach., Methods: Using PROMMTT data and multilevel logistic regression to adjust for center effects, we related in-hospital mortality to the early receipt of plasma or platelets within the first three to six transfusion units (including RBCs) and 2.5 hours of admission. We adjusted for the same covariates as in our previous report: Injury Severity Score (ISS), age, time and total number of blood product transfusions upon entry to the analysis cohort, and bleeding from the head, chest, or limb., Results: Of 1,245 PROMMTT patients, 619 were eligible for this analysis. Early plasma was associated with decreased 24-hour and 30-day mortality (adjusted odds ratios of 0.47 [p = 0.009] and 0.44 [p = 0.002], respectively). Too few patients (24) received platelets early for meaningful assessment. In the subgroup of 222 patients receiving no early plasma but continuing transfusions beyond Hour 2.5, achieving gradually balanced plasma and platelet:RBC ratios of 1:2 or greater by Hour 4 was not associated with 30-day mortality (adjusted odds ratios of 0.9 and 1.1, respectively). There were no significant center effects., Conclusion: Plasma transfusion early in resuscitation had a protective association with mortality, whereas delayed but gradually balanced transfusion ratios did not. Further research will require considerably larger numbers of patients receiving platelets early.

Background: There are few clinical data to guide the use of cryoprecipitate in severely injured trauma patients. Cryoprecipitate is a rich source of fibrinogen and has been associated with improved survival in animal as well as limited human studies. Our objectives were to identify patterns and predictors of cryoprecipitate use and determine whether transfusing cryoprecipitate was associated with improved survival., Methods: This secondary analysis of 1,238 of 1,245 PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study patients who had timed transfusion data included 359 (29%) who received cryoprecipitate. For this analysis, one dose of cryoprecipitate was defined as 10 U. Unadjusted predictors of cryoprecipitate use were identified using logistic regression. Multivariable time-dependent Cox models were performed to examine the association of cryoprecipitate on time to in-hospital death., Results: Cryoprecipitate use varied significantly by center, ranging from 7% to 82%. Among patients who received cryoprecipitate, the median number of units infused by 24 hours was 10 (interquartile range, 10-20). The median time from admission to first cryoprecipitate unit was 2.7 hours (interquartile range, 1.7-4.4 hours). Of those who died of a hemorrhagic death within 6 hours of admission, 72% received no cryoprecipitate. Other unadjusted predictors of cryoprecipitate use included Injury Severity Score (ISS), initial fibrinogen levels, base deficit, international normalized ratio, prothrombin time/partial thromboplastin time, hemoglobin, damage-control surgery, and surgical intervention of the chest and abdomen. Cryoprecipitate use was not associated with in-hospital mortality after adjusting for initial pH, initial hemoglobin, emergency department systolic blood pressure, emergency department Glasgow Coma Scale (GCS) score, blood product use, ISS, and center., Conclusion: Ten US Level 1 trauma centers vary greatly in their timing and use of cryoprecipitate in severely injured trauma patients. We could not identify any association of cryoprecipitate use with in-hospital mortality, although most patients did not receive this product. Randomized controlled studies are needed to determine if cryoprecipitate (or fibrinogen concentrates) have a beneficial effect.

Background: Acute lung injury following trauma resuscitation remains a concern despite recent advances. With the use of the PROMMTT study population, the risk of hypoxemia and potential modifiable risk factors are studied., Methods: Patients with survival for 24 hours or greater with at least one intensive care unit day were included in the analysis. Hypoxemia was categorized using the Berlin definition for adult respiratory distress syndrome: none (PaO₂-to-FIO₂ ratio [P/F] > 300 mm Hg), mild (P/F, 201-300 mm Hg), moderate (P/F, 101-200 mm Hg) or severe (P/F ≤ 100 mm Hg). The cohort was dichotomized into those with none or mild hypoxemia and those with moderate or severe injury. Early resuscitation was defined as that occurring 0 hour to 6 hours from arrival; late resuscitation was defined as that occurring 7 hours to 24 hours. Multivariate logistic regression models were developed controlling for age, sex, mechanisms of injury, arrival physiology, individual Abbreviated Injury Scale (AIS) scores, blood transfusions, and crystalloid administration., Results: Of the patients 58.7% (731 of 1,245) met inclusion criteria. Hypoxemia occurred in 69% (mild, 24%; moderate, 28%; severe, 17%). Mortality was highest (24%) in the severe group. During early resuscitation (0-6 h), logistic regression revealed age (odd ratio [OR], 1.02; 95% confidence interval [CI], 1.00-1.04), chest AIS score (OR, 1.31; 95% CI, 1.10-1.57), and intravenously administered crystalloid fluids given in 500 mL increments (OR, 1.12; 95% CI, 1.01-1.25) as predictive of moderate or severe hypoxemia. During late resuscitation, age (OR, 1.02; 95% CI, 1.00-1.04), chest AIS score (OR, 1.33; 95% CI, 1.11-1.59), and crystalloids given during this period (OR, 1.05; 95% CI, 1.01-1.10) were also predictive of moderate-to-severe hypoxemia. Red blood cell, plasma, and platelet transfusions (whether received during early or late resuscitation) failed to demonstrate an increased risk of developing moderate/severe hypoxemia., Conclusion: Severe chest injury, increasing age, and crystalloid-based resuscitation, but not blood transfusions, were associated with increased risk of developing moderate-to-severe hypoxemia following injury.

Background: The Focused Assessment with Sonography for Trauma (FAST) examination is an important variable in many retrospective trauma studies. The purpose of this study was to devise an imputation method to overcome missing data for the FAST examination. Owing to variability in patients' injuries and trauma care, these data are unlikely to be missing completely at random, raising concern for validity when analyses exclude patients with missing values., Methods: Imputation was conducted under a less restrictive, more plausible missing-at-random assumption. Patients with missing FAST examinations had available data on alternate, clinically relevant elements that were strongly associated with FAST results in complete cases, especially when considered jointly. Subjects with missing data (32.7%) were divided into eight mutually exclusive groups based on selected variables that both described the injury and were associated with missing FAST values. Additional variables were selected within each group to classify missing FAST values as positive or negative, and correct FAST examination classification based on these variables was determined for patients with nonmissing FAST values., Results: Severe head/neck injury (odds ratio [OR], 2.04), severe extremity injury (OR, 4.03), severe abdominal injury (OR, 1.94), no injury (OR, 1.94), other abdominal injury (OR, 0.47), other head/neck injury (OR, 0.57), and other extremity injury (OR, 0.45) groups had significant ORs for missing data; the other group's OR was not significant (OR, 0.84). All 407 missing FAST values were imputed, with 109 classified as positive. Correct classification of nonmissing FAST results using the alternate variables was 87.2%., Conclusion: Purposeful imputation for missing FAST examinations based on interactions among selected variables assessed by simple stratification may be a useful adjunct to sensitivity analysis in the evaluation of imputation strategies under different missing data mechanisms. This approach has the potential for widespread application in clinical and translational research, and validation is warranted.

Background: Missing data are inherent in clinical research and may be especially problematic for trauma studies. This study describes a sensitivity analysis to evaluate the impact of missing data on clinical risk prediction algorithms. Three blood transfusion prediction models were evaluated using an observational trauma data set with valid missing data., Methods: The PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study included patients requiring one or more unit of red blood cells at 10 participating US Level I trauma centers from July 2009 to October 2010. Physiologic, laboratory, and treatment data were collected prospectively up to 24 hours after hospital admission. Subjects who received 10 or more units of red blood cells within 24 hours of admission were classified as massive transfusion (MT) patients. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation. A sensitivity analysis for missing data was conducted to determine the upper and lower bounds for correct classification percentages., Results: PROMMTT study enrolled 1,245 subjects. MT was received by 297 patients (24%). Missing percentage ranged from 2.2% (heart rate) to 45% (respiratory rate). Proportions of complete cases used in the MT prediction models ranged from 41% to 88%. All models demonstrated similar correct classification percentages using complete case analysis and multiple imputation. In the sensitivity analysis, correct classification upper-lower bound ranges per model were 4%, 10%, and 12%. Predictive accuracy for all models using PROMMTT data was lower than reported in the original data sets., Conclusion: Evaluating the accuracy clinical prediction models with missing data can be misleading, especially with many predictor variables and moderate levels of missingness per variable. The proposed sensitivity analysis describes the influence of missing data on risk prediction algorithms. Reporting upper-lower bounds for percent correct classification may be more informative than multiple imputation, which provided similar results to complete case analysis in this study.

Background: Prediction of outcome after injury is fraught with uncertainty and statistically beset by misspecified models. Single-time point regression only gives prediction and inference at one time, of dubious value for continuous prediction of ongoing bleeding. New statistical machine learning techniques such as SuperLearner (SL) exist to make superior prediction at iterative time points while evaluating the changing relative importance of each measured variable on an outcome. This then can provide continuously changing prediction of outcome and evaluation of which clinical variables likely drive a particular outcome., Methods: PROMMTT data were evaluated using both naive (standard stepwise logistic regression) and SL techniques to develop a time-dependent prediction of future mortality within discrete time intervals. We avoided both underfitting and overfitting using cross validation to select an optimal combination of predictors among candidate predictors/machine learning algorithms. SL was also used to produce interval-specific robust measures of variable importance measures (VIM resulting in an ordered list of variables, by time point) that have the strongest impact on future mortality., Results: Nine hundred eighty patients had complete clinical and outcome data and were included in the analysis. The prediction of ongoing transfusion with SL was superior to the naive approach for all time intervals (correlations of cross-validated predictions with the outcome were 0.819, 0.789, 0.792 for time intervals 30-90, 90-180, 180-360, >360 minutes). The estimated VIM of mortality also changed significantly at each time point., Conclusion: The SL technique for prediction of outcome from a complex dynamic multivariate data set is superior at each time interval to standard models. In addition, the SL VIM at each time point provides insight into the time-specific drivers of future outcome, patient trajectory, and targets for clinical intervention. Thus, this automated approach mimics clinical practice, changing form and content through time to optimize the accuracy of the prognosis based on the evolving trajectory of the patient.

Background: Several predictive models have been developed to identify trauma patients who have had severe hemorrhage (SH) and may need a massive transfusion (MT) protocol. However, almost all these models define SH as the transfusion of 10 or more units of red blood cells (RBCs) within 24 hours of emergency department admission (also known as MT). This definition excludes some patients with SH, especially those who die before a 10th unit of RBCs could be transfused, which calls the validity of these prediction models into question. We show how a latent class model could improve the accuracy of identifying the SH patients., Methods: Modeling SH classification as a latent variable, we estimate the posterior probability of a patient in SH based on emergency department admission variables (systolic blood pressure, heart rate, pH, hemoglobin), the 24-hour blood product use (plasma/RBC and platelet/RBC ratios), and 24-hour survival status. We define the SH subgroup as those having a posterior probability of 0.5 or greater. We compare our new classification of SH with that of the traditional MT using data from PROMMTT study., Results: Of the 1,245 patients, 913 had complete data, which were used in the latent class model. About 25.3% of patients were classified as SH. The overall agreement between the MT and SH classifications was 83.8%. However, among 49 patients who died before receiving the 10th unit of RBCs, 41 (84%) were classified as SH. Seven (87.5%) of the remaining eight patients who were not classified as SH had head injury., Conclusion: Our definition of SH based on the aforementioned latent class model has an advantage of improving on the traditional MT definition by identifying SH patients who die before receiving the 10th unit of RBCs. We recommend further improvements to more accurately classify SH patients, which could replace the traditional definition of MT for use in developing prediction algorithms.

Background: In the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study, waiver of consent was used because previous literature reported low response rates and subsequent bias. The goal of this article was to examine the rationale and tradeoffs of using waiver of consent in PROMMTT., Methods: PROMMTT enrolled trauma patients receiving at least 1 U of red blood cells within 6 hours after admission at 10 US Level 1 trauma centers. Local institutional review boards (IRBs) from all sites approved the study. Site 8 was required by their IRB to attempt consent but was allowed to retain data on patients unable to be consented., Results: Of 121 subjects enrolled at Site 8, 55 consents were obtained (46%), and no patient or legally authorized representative refused to give consent. Of the patients, 36 (30%) died, and 6 (5%) were discharged before consent could be attempted. Consent was attempted but not possible among 24 patients (20%). Of the 10 clinical sites, 6 of the local IRBs approved collection of residual blood samples, 1 had previous approval to collect timed blood samples under a separate protocol, and 3 reported that their local IRBs would not approve collection of residual blood under a waiver of consent., Conclusion: Waiver of consent was used in PROMMTT because of the potential adverse impact of consent refusals; however, there were no refusals. If the IRB for Site 8 had required withdrawal of patients unable to consent and destruction of their data, a serious bias would likely have been introduced. Other tradeoffs included a reduction in sites participating in residual blood collection and a smaller than expected amount of residual blood collected among sites operating under a waiver of consent. Noninterventional emergency research studies should consider these potential tradeoffs carefully before deciding whether waiver of consent would best achieve the goals of a study.

Background: Acute traumatic coagulopathy (ATC) occurs after severe injury and shock and is associated with increased bleeding, morbidity, and mortality. The effects of ATC and hemostatic resuscitation on outcome are not well-explored. The PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study provided a unique opportunity to characterize coagulation and the effects of resuscitation on ATC after severe trauma., Methods: Blood samples were collected upon arrival on a subset of PROMMTT patients. Plasma clotting factor levels were prospectively assayed for coagulation factors. These data were analyzed with comprehensive PROMMTT clinical data., Results: There were 1,198 patients with laboratory results, of whom 41.6% were coagulopathic. Using international normalized ratio of 1.3 or greater, 41.6% of patients (448) were coagulopathic, while 20.5% (214) were coagulopathic using partial thromboplastin time of 35 or greater. Coagulopathy was primarily associated with a combination of an Injury Severity Score (ISS) of greater than 15 and a base deficit (BD) of less than -6 (p < 0.05). Regression modeling for international normalized ratio-based coagulopathy shows that prehospital crystalloid (odds ratio [OR], 1.05), ISS (OR, 1.03), Glasgow Coma Scale (GCS) score (OR, 0.93), heart rate (OR, 1.08), systolic blood pressure (OR, 0.96), BD (OR, 0.92), and temperature (OR, 0.84) were significant predictors of coagulopathy (all p < 0.03). A subset of 165 patients had blood samples collected and coagulation factor analysis performed. Elevated ISS and BD were associated with elevation of aPC and depletion of factors (all p < 0.05). Reductions in factors I, II, V, VIII and an increase in aPC drive ATC (all p < 0.04). Similar results were found for partial thromboplastin time-defined coagulopathy., Conclusion: ATC is associated with the depletion of factors I, II, V, VII, VIII, IX, and X and is driven by the activation of the protein C system. These data provide additional mechanistic understanding of the drivers of coagulation abnormalities after injury. Further understanding of the drivers of ATC and the effects of resuscitation can guide factor-guided resuscitation and correction of coagulopathy after injury.

Background: The classic definition of massive transfusion, 10 or more units of red blood cells (RBCs) in 24 hours, has never been demonstrated as a valid surrogate for severe hemorrhage and can introduce survival bias. In addition, the definition fails to capture other products that the clinician may have immediately available, and may use, during the initial resuscitation. Assuming that units of resuscitative fluids reflect patient illness, our objective was to identify a rate of resuscitation intensity (RI) that could serve as an early surrogate of sickness for patients with substantial bleeding after injury., Methods: Adult patients surviving at least 30 minutes after admission and receiving one or more RBCs within 6 hours of admission from 10 US Level 1 trauma centers were enrolled in the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study. Total fluid units were calculated as the sum of the number of crystalloid units (1 L = 1 U), colloids (0.5 L = 1 U), and blood products (1 RBC = 1 U, 1 plasma = 1 U, 6 pack platelets = 1 U). Univariable and multivariable logistic regressions were used to evaluate associations between RI and 6-hour mortality, adjusting for age, center, penetrating injury, weighted Revised Trauma Score (RTS), and Injury Severity Score (ISS)., Results: A total of 1,096 eligible patients received resuscitative fluids within 30 minutes, including 620 transfused with blood products. Despite varying products used, the total fluid RI was similar across all sites (3.2 ± 2.5 U). Patients who received four or more units of any resuscitative fluid had a 6-hour mortality rate of 14.4% versus 4.5% in patients who received less than 4 U. The adjusted odds ratio of 6-hour mortality for patients receiving 4 U or more within 30 minutes was 2.1 (95% confidence interval, 1.2-3.5)., Conclusion: Resuscitation with four or more units of any fluid was significantly associated with 6-hour mortality. This study suggests that early RI regardless of fluid type can be used as a surrogate for sickness and mortality in severely bleeding patients.

Background: The impact of do-not-resuscitate (DNR) orders has not been systematically evaluated in acute trauma research. We determined the frequency, timing, and impact on mortality-based effect estimates for patients with DNR orders in the Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study., Methods: Trauma patients surviving at least 30 minutes and transfused one or greater unit of red blood cell within 6 hours of admission (n = 1,245) from 10 Level 1 centers were enrolled. We report descriptive statistics and results from survival analysis to compare the association of blood product transfusion ratios with outcome defined as mortality and as a composite, DNR, and death., Results: DNRs were reported for 95 patients (7.6%), with 94 in-hospital deaths. There were 172 deaths without DNRs. Of 90 known DNR order times, the median was 53 hours (interquartile range, 9-186 hours) after admission; the median DNR-to-death time was 10 hours (2-32 hours). DNRs were for comfort measures only (43%), no cardiopulmonary resuscitation (40%), and no intubation or cardiopulmonary resuscitation (16%). Compared with the 116 non-DNR deaths that occurred after the earliest DNR order (2 hours), the DNR decedents were significantly older with a less severe base deficit, fewer red blood cell and plasma transfusions, and a later median time of death (98 [21-230] hours vs. 17 [4-91] hours). In multivariable Cox models that accounted for time-varying blood product ratios, the associations were consistent, regardless of whether outcome was defined as mortality or the composite., Conclusion: DNR orders were instituted after the 24-hour period of highest mortality risk and more often in older patients not in severe shock. Findings from the primary PROMMTT analyses of the impact of blood product ratios on survival did not materially change when the original mortality outcome was redefined as a composite of DNR or death. DNR orders are potentially an important mediating variable that should be systematically evaluated in trauma research.

Introduction: Focused assessment with sonography for trauma (FAST) is commonly used to facilitate the timely diagnosis of life-threatening hemorrhage in injured patients. Most patients with positive findings on FAST require laparotomy. Although it is assumed that an increasing time to operation (T-OR) leads to higher mortality, this relationship has not been quantified. This study sought to determine the impact of T-OR on survival in patients with a positive FAST who required emergent laparotomy., Methods: We retrospectively analyzed patients from the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study who underwent laparotomy within 90 minutes of presentation and had a FAST performed. Cox proportional hazards models including Injury Severity Score (ISS), age, base deficit, and hospital site were created to examine the impact of increasing T-OR on in-hospital survival at 24 hours and 30 days. The impact of time from the performance of the FAST examination to operation (TFAST-OR) on in-hospital mortality was also examined using the same model., Results: One hundred fifteen patients met study criteria and had complete data. Increasing T-OR was associated with increased in-hospital mortality at 24 hours (hazard ratio [HR], 1.50 for each 10-minute increase in T-OR; confidence interval [CI], 1.14-1.97; p = 0.003) and 30 days (HR, 1.41; CI, 1.18-2.10; p = 0.002). Increasing TFAST-OR was also associated with higher in-hospital mortality at 24 hours (HR, 1.34; CI, 1.03-1.72; p = 0.03) and 30 days (HR, 1.40; CI, 1.06-1.84; p = 0.02)., Conclusion: In patients with a positive FAST who required emergent laparotomy, delay in operation was associated with increased early and late in-hospital mortality. Delays in T-OR in trauma patients with a positive FAST should be minimized.

Objective: To relate in-hospital mortality to early transfusion of plasma and/or platelets and to time-varying plasma:red blood cell (RBC) and platelet:RBC ratios., Design: Prospective cohort study documenting the timing of transfusions during active resuscitation and patient outcomes. Data were analyzed using time-dependent proportional hazards models., Setting: Ten US level I trauma centers., Patients: Adult trauma patients surviving for 30 minutes after admission who received a transfusion of at least 1 unit of RBCs within 6 hours of admission (n = 1245, the original study group) and at least 3 total units (of RBCs, plasma, or platelets) within 24 hours (n = 905, the analysis group)., Main Outcome Measure: In-hospital mortality., Results: Plasma:RBC and platelet:RBC ratios were not constant during the first 24 hours (P < .001 for both). In a multivariable time-dependent Cox model, increased ratios of plasma:RBCs (adjusted hazard ratio = 0.31; 95% CI, 0.16-0.58) and platelets:RBCs (adjusted hazard ratio = 0.55; 95% CI, 0.31-0.98) were independently associated with decreased 6-hour mortality, when hemorrhagic death predominated. In the first 6 hours, patients with ratios less than 1:2 were 3 to 4 times more likely to die than patients with ratios of 1:1 or higher. After 24 hours, plasma and platelet ratios were unassociated with mortality, when competing risks from nonhemorrhagic causes prevailed., Conclusions: Higher plasma and platelet ratios early in resuscitation were associated with decreased mortality in patients who received transfusions of at least 3 units of blood products during the first 24 hours after admission. Among survivors at 24 hours, the subsequent risk of death by day 30 was not associated with plasma or platelet ratios.

Background: Early predictors of massive transfusion (MT) would prevent undertriage of patients likely to require MT. This study validates triggers using the Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study., Methods: All enrolled patients in PROMMTT were analyzed. The initial emergency department value for each trigger (international normalized ratio [INR], systolic blood pressure, hemoglobin, base deficit, positive result for Focused Assessment for the Sonography of Trauma examination, heart rate, temperature, and penetrating injury mechanism) was compared for patients receiving MT (≥ 10 U of packed red blood cells in 24 hours) versus no MT. Adjusted odds ratios (ORs) for MT are reported using multiple logistic regression. If all triggers were known, a Massive Transfusion Score (MTS) was created, with 1 point assigned for each met trigger., Results: A total of 1,245 patients were prospectively enrolled with 297 receiving an MT. Data were available for all triggers in 66% of the patients including 67% of the MTs (199 of 297). INR was known in 87% (1,081 of 1,245). All triggers except penetrating injury mechanism and heart rate were valid individual predictors of MT, with INR as the most predictive (adjusted OR, 2.5; 95% confidence interval, 1.7-3.7). For those with all triggers known, a positive INR trigger was seen in 49% receiving MT. Patients with an MTS of less than 2 were unlikely to receive MT (negative predictive value, 89%). If any two triggers were present (MTS ≥ 2), sensitivity for predicting MT was 85%. MT was present in 33% with an MTS of 2 greater compared with 11% of those with MTS of less than 2 (OR, 3.9; 95% confidence interval, 2.6-5.8; p < 0.0005)., Conclusion: Parameters that can be obtained early in the initial emergency department evaluation are valid predictors for determining the likelihood of MT., Level of Evidence: Diagnostic, level II.