Scoring of pediatric orthopaedic polytrauma: correlations of different injury scoring systems and prognosis for hospital course

Trauma scoring systems were compared among themselves and to recovery variables in a cohort of 91 pediatric polytrauma patients with orthopaedic injuries. They included the Trauma Score (TS), Revised Trauma Score (RTS), Injury Severity Score (ISS), Modified Abbreviated Injury Severity Scale (MISS), Pediatric Trauma Score (PTS), and TRISS-b survival statistic. Significant correlations between scoring systems and hospital course parameters existed. TRISS-b had the strongest correlation for days in the intensive care unit and total complications (r2 = 0.59, 0.58). PTS correlated poorly with recovery variables when compared to other scoring systems. The TS correlated most strongly with ventilatory days and complications of immobilization (r2 = 0.77, 0.58). The TS should be used early in the assessment of the pediatric polytrauma patient, along with the TRISS-b statistic. If they predict prolonged intensive care unit and ventilatory days and hospital complications, operative fracture management should be strongly considered.     

Is a full team required for emergency management of pediatric trauma?

Pediatric trauma centers often do not meet the guidelines requiring a trauma team as recommended by the American Academy of Pediatrics (AAP). We reviewed our experience with a team consisting of a pediatric emergency physician, resident, nurse, and respiratory therapist. The surgical and pediatric critical care residents and staff were available within 5 minutes. We conducted a retrospective chart review of 146 patients (aged 8.1 +/- 4.8 years) between 1987 and 1989, with Injury Severity Scores (ISS) greater than or equal to 16 or admitted to the pediatric critical care unit. The time of presentation, surgical services consulted, and the nature of the injury were obtained from chart review. The Pediatric Trauma Score (PTS), the Revised Trauma Score (RTS), the Injury Severity Score (ISS), Glasgow Coma Scale (GCS) score, and Pediatric Risk of Mortality (PRISM) were used to determine the severity of insult and physiologic derangement on admission. The Modified Injury Severity Score (MISS) was determined and the Delta score for Disability Assessment was assigned at discharge. The Delta score was also determined at 3-month intervals up to one year. The probability of survival (Ps) was calculated, using the ISS and RTS. The Z statistic for this group of patients was then determined, using the Major Trauma Outcome Study (MTOS) methodology. The percentages of patients who were normal, disabled, and dead were 61%, 31.5%, and 7.5%, respectively, at 6 months follow-up. Eleven deaths were expected based on PRISM and TRISS analysis. Our mortality and morbidity figures were comparable with those of centers with teams based on AAP guidelines.(ABSTRACT TRUNCATED AT 250 WORDS)     

Predicting inpatient mortality for pediatric trauma patients with blunt injuries: a better alternative

PURPOSE: The aim of this study was to identify significant independent predictors of inpatient mortality rates for pediatric victims of blunt trauma and to develop a formula for predicting the probability of inpatient mortality for these patients. METHODS: Emergency department and inpatient data from 2,923 pediatric victims of blunt injury in the New York State Trauma Registry in 1994 and 1995 were used to explore the relationship between patient risk factors and mortality rate. A stepwise logistic regression model with P<.05 was developed using survival status asthe dependent variable. Independent variables included are elements of the Pediatric Trauma Score (PTS), additional elements from the Revised Trauma Score (RTS), the motor response and eye opening components of the Glasgow Coma Scale (GCS), age-specific systolic blood pressure, the AVPU score, and 2 measures of anatomic injury severity (the Injury Severity Score [ISS] and the International Classification of Disease, Ninth Revision-based Injury Severity Score [ICISS]). RESULTS: The only significant independent predictors of severity that emerged were the ICISS, no motor response (best motor response = 1) from the GCS, and the unresponsive component from the AVPU score. The statistical model exhibited an excellent fit (C statistic = .964). The specificity associated with the prediction of inpatient mortality rate based on the presence of 1 or more of these risk factors was .926, and the sensitivity was .944. CONCLUSION: The best independent predictors of inpatient mortality rate for pediatric trauma patients with blunt injuries include variables not specifically contained in the PTS or the RTS: ICISS, no motor response (best motor response = 1) from the GCS, and the unresponsive component of the AVPU score.     

Comparing logistic models based on modified GCS motor component with other prognostic tools in prediction of mortality: results of study in 7226 trauma patients

A simple reproducible and sensitive prognostic trauma tool is still needed. In this article we have introduced modified GCS motor response (MGMR) and evaluated the performance of logistic models based on this variable. The records of 8452 trauma patients admitted to major hospitals of Tehran from 1999 to 2000 were analysed. 7226 records with known outcome were included in our study. Logistic models based on outcome (death versus survival) as a dependent variable and Injury Severity Score (ISS), Revised Trauma Score (RTS), Glasgow Coma Scale (GCS), GCS motor component (GMR) and MGMR (following command [=2], movement but not following [=1] command and without movement [=0]) were compared based on their accuracy and area under the Receiver Operating Characteristic (ROC) curve. The accuracy of the Trauma and Injury Severity Score (TRISS), RTS, GCS, GMR and MGMR models were almost the same. Considering both the area under the ROC curve and accuracy, the age included MGMR model was also comparable with other age included models (RTS+age, GCS+age, GMR+age). We concluded that although in some situations we need more sophisticated models, should our results be reproducible in other populations, MGMR (with or without age added) model may be of considerable practical value.     

Clinical retrospective and comparative study on diaphragm injuries in 46 cases

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A comparison of the abilities of nine scoring algorithms in predicting mortality

OBJECTIVE: The purpose of this study was to compare the abilities of nine Abbreviated Injury Scale (AIS)- and (ICD-9)-based scoring algorithms in predicting mortality. METHODS: The scores collected on 76,871 incidents consist of four AIS-based algorithms (Injury Severity Score [ISS], New Injury Severity Score, Anatomic Profile Score [APS], and maximum AIS [maxAIS]), their four ICD to AIS mapped counterparts, and the ICD-9-based ISS (ICISS). A 10-fold cross-validation was performed and area under the receiver operating characteristic curve was used to determine algorithm discrimination. Hosmer-Lemeshow statistics were computed to gauge goodness-of-fit, and model refinement measured variance of predicted probabilities. RESULTS: Overall, the ICISS has the best discrimination and model refinement, whereas the APS has the best Hosmer-Lemeshow performance. ICD-9 to AIS mapped scores have worse discrimination than their AIS-based counterparts, but still show moderate performance. CONCLUSION: Differences in performance were relatively small. Complex scores such as the ICISS and the APS provide improvement in discrimination relative to the maxAIS and the ISS. Trauma registries should move to include the ICISS and the APS. The ISS and maxAIS perform moderately well and have bedside benefits.     

Mortality prognostic factors in chest injury

1,026 multiple trauma patients (P) were compared to P with chest injuries (PCT) (407). Severity indices were related to type of thoracic injury and mortality. The Injury Severity Score (ISS), Glasgow Coma Scale (GCS), Trauma Score (TS), CHOP, and the Respiratory Index (RI) were used. The mortality rate of P was 27.1% but increased to 32.9% for PCT (p less than 0.05). We noted that mortality rate was highly dependent on major chest trauma: 68.6% for flail chest (FC), 56% for lung contusion (LC), 42.3% for hemothorax (HA), and 38.1% for pneumothorax (PN). ISS and RI scores for PCT survivors were greater than ISS + RI scores for P survivors (p less than 0.05 and p less than 0.01). ISS values for LC, HA, and PN PCT survivors were greater than the ISS of P survivors (p less than 0.01). Nonsurviving PCTs, especially those with lung contusion, showed a highly significant increase in ISS and RI scores.     

Incorporating recent advances to make the TRISS approach universally available

BACKGROUND: The Trauma and Injury Severity Score (TRISS), used to garner predictions of survival from the Injury Severity Score (ISS), the Revised Trauma Score (RTS, for physiologic reserve), and age is difficult for many trauma facilities to compute because it requires 8 to 10 variables and ISS depends on the specialized Abbreviated Injury Scale (AIS) scale rather than the International Classification of Diseases scale (ICD-9). It has been shown that metrics describing a patient's worst injury (WORSTSRR) are a powerful predictor of survival (regardless of coding type, AIS versus ICD-9) and that the Glasgow Coma Scale (GCS) motor component contains the majority of the information found in the full GCS score. This study hypothesized that the TRISS approach could be made more predictive and efficient with fewer variables by incorporating these advances. METHODS: A total of 310,958 patients with nonmissing TRISS variables were subset from the National Trauma Data Bank (NTDB). Logistic regression was used to model mortality as a function of anatomic, physiologic and age variables. A traditional TRISS model was computed (with NTDB-derived coefficients) that uses ISS, RTS, age index, and mechanism to predict survival. Four smaller three- or four-variable models employed the ICD-9 WORSTSRR, the GCS motor component, and age (both continuously and dichotomously). Two of the four models also use mechanism. These models were compared using the concordance index (c-index, a measure of model discrimination) and the pseudo-R statistic (estimates proportion of variance explained). RESULTS: Each experimental model (two models with 3 variables and two models with 4 variables) have superior discrimination and explain more variance than the traditional TRISS model that employs 8-10 variables. CONCLUSIONS: Recent advances in anatomic and physiologic scoring markedly simplify TRISS-type models at no cost to prediction. This approach uses routinely available data, requires up to seven fewer terms, and predicts at least as well as the original TRISS. These findings could increase the availability of accurate trauma scoring tools to smaller trauma facilities.     

Predictors of mortality in adult trauma patients: the physiologic trauma score is equivalent to the Trauma and Injury Severity Score

Background:

Several statistical models (Trauma and Injury Severity Score [TRISS], New Injury Severity Score [NISS], and the International Classification of Disease, Ninth Revision-based Injury Severity Score [ICISS]) have been developed over the recent decades in an attempt to accurately predict outcomes in trauma patients. The anatomic portion of these models makes them difficult to use when performing a rapid initial trauma assessment. We sought to determine if a Physiologic Trauma Score, using the systemic inflammatory response syndrome (SIRS) score in combination with other commonly used indices, could accurately predict mortality in trauma.

Study Design:

Prospective data were analyzed in 9,539 trauma patients evaluated at a Level I Trauma Center over a 30-month period (January 1997 to July 1999). A SIRS score (1 to 4) was calculated on admission (1 point for each: temperature >38°C or <36°C, heart rate >90 beats per minute, respiratory rate >20 breaths per minute, neutrophil count > 12,000 or < 4,000. SIRS score, Injury Severity Score (ISS), Revised Trauma Score (RTS), TRISS, Glasgow Coma Score, age, gender, and race were used in logistic regression models to predict trauma patients’ risk of death. The area under the receiver-operating characteristic curves of sensitivity versus 1-specificity was used to assess the predictive ability of the models.

Results:

The study cohort of 9,539 trauma patients (of which 7,602 patients had complete data for trauma score calculations) had a mean ISS of 9 ± 9 (SD) and mean age of 37 ± 17 years. SIRS (SIRS score ≥ 2) was present in 2,165 of 7,602 patients (28.5%). In single-variable models, TRISS and ISS were most predictive of outcomes. A multiple-variable model, Physiologic Trauma Score combining SIRS score with Glasgow Coma Score and age (Hosmer-Lemenshow CHI-SQUARE = 4.74) was similar to TRISS and superior to ISS in predicting mortality. The addition of ISS to this model did not significantly improve its predictive ability.

Conclusions:

A new statistical model (Physiologic Trauma Score), including only physiologic variables (admission SIRS score combined with Glasgow Coma Score and age) and easily calculated at the patient bedside, accurately predicts mortality in trauma patients. The predictive ability of this model is comparable to other complex models that use both anatomic and physiologic data (TRISS, ISS, and ICISS).     

The effect of patient age upon survival in pediatric trauma

Developmental changes in the anatomy and physiology of growing children are thought to improve the survivability of older children to significant injury. The effect of age upon survival, however, is poorly defined. Data for 4,615 patients less than 15 years old from a statewide trauma center registry were analyzed. Injury and survival were characterized by Abbreviated Injury Scale (AIS, 1985 revision), Injury Severity Score (ISS), Revised Trauma Score (RTS), and probability of survival [P(s)] and Z by TRISS. Patients were separated into age groups of 0 through 4, 5 through 9, and 10 through 14 years. The survival rate for patients with a maximum AIS 3 for any region was significantly higher in the 10-14-year age group. There were no significant differences in survival rates from head, thoracic, and abdominal injuries stratified by AIS among the three age groups. Survival rates for ISS cohorts were consistently lowest in the 0-4-year age group, but differences failed to reach significance. Survival for RTS and P(s) intervals were similar for all ages. The Z statistic reached significance for all children (Z = 4.717, W = 1.049), and for each group (Z = 2.203-3.029). Corresponding values of the W statistic suggest approximately one additional unexpected survivor per 100 admitted children when compared with the Major Trauma Outcome Study. Logistic regression for patients with all data required for TRISS showed no significant effect for any of the three age groups. We conclude that for this patient set, survival after childhood injury is independent of the age groups used in this study, after controlling for injury severity.     

Validation of international trauma scoring systems in urban trauma centres in India

IntroductionIn the Lower-Middle Income Country setting, we validate trauma severity scoring systems, namely Injury Severity Score (ISS), New Injury Severity Scale (NISS) score, the Kampala Trauma Score (KTS), Revised Trauma Score (RTS) score and the TRauma Injury Severity Score (TRISS) using Indian trauma patients.Patients and methodsFrom 1 September 2013 to 28 February 2015, we conducted a prospective multi-centre observational cohort study of trauma patients in four Indian university hospitals, in three megacities, Kolkata, Mumbai and Delhi. All adult patients presenting to the casualty department with a history of injury and who were admitted to inpatient care were included. The primary outcome was in-hospital mortality within 30-days of admission. The sensitivity and specificity of each score to predict inpatient mortality within 30 days was assessed by the areas under the receiver operating characteristic curve (AUC). Model fit for the performance of individual scoring systems was accomplished by using the Akaike Information criterion (AIC).ResultsIn a registry of 8791 adult trauma patients, we had a cohort of 7197 patients eligible for the study. 4091 (56.8%)patients had all five scores available and was the sample for a complete case analysis. Over a 30-day period, the scores (AUC) was TRISS (0.82), RTS (0.81), KTS (0.74), NISS (0.65) and ISS (0.62). RTS was the most parsimonious model with the lowest AIC score. Considering overall mortality, both physiologic scores (RTS, KTS) had better discrimination and goodness-of-fit than ISS or NISS. The ability of all Injury scores to predict early mortality (24 h) was better than late mortality (30 day).ConclusionOn-admission physiological scores outperformed the more expensive anatomy-based ISS and NISS. The retrospective nature of ISS and TRISS score calculations and incomplete imaging in LMICs precludes its use in the casualty department of LMICs. They will remain useful for outcome comparison across trauma centres. Physiological scores like the RTS and KTS will be the practical score to use in casualty departments in the urban Indian setting, to predict early trauma mortality and improve triage.     

Functional outcome of pediatric trauma patients identified as 'non-salvageable survivors'

A retrospective study of 305 pediatric trauma patients seen over 17 months was undertaken to evaluate the functional outcome of patients categorized as "non-salvageable survivors" (NSS). Functional outcome was determined by Denver Developmental Screen Tests (DDST) for children less than 5 years of age and Rappaport Severity Rating Scale (RDRS) for those 5 years old and older. Each patient was assigned Abbreviated Injury Scores (AIS). Injury Severity Score (ISS), Glasgow Coma Scale (GCS), and Trauma Score (TS). The total number of patients classified as severe was 65 (21%), and 13 were classified as non-salvageable, with seven non-salvageable survivors and six non-preventable deaths. Our study suggests that current trauma scoring systems tend to overestimate the non-salvageable population. Those identified as non-salvageable and who survived have a high probability of meaningful functional recovery. Current trauma scoring systems are in need of revision to better identify non-salvageable survivors and those children who will not make a meaningful neurologic recovery.     

Cost factors in Canadian pediatric trauma.

OBJECTIVES: To estimate the costs of Canadian pediatric trauma and identify cost predictors. DESIGN: A chart review. SETTING: A regional trauma centre. STUDY MATERIAL: The charts of all 221 children who suffered traumatic injuries with an Injury Severity Score (ISS) of 4 or more seen over 6 years at a regional trauma centre. MAIN OUTCOME MEASURES: Patient data, injury data, all hospital-based costs, excluding nursing, food and medication costs. RESULTS: Mean (and standard deviation) patient age was 12.8 (5) years. Sixty percent were boys. Motor vehicle accidents (MVAs) accounted for 71% of the injuries, followed by falls (11%). The mean (and SD) total cost of care was Can$7,582 (Can$12,370), and the cost of media was Can$2,666. Total cost correlated directly with age (r = 0.29, p < 0.001) and Injury Severity Score (ISS) (r = 0.34, p < 0.001) and inversely with the Pediatric Trauma Score (PTS) (r = -0.20, p = 0.003). The presence of extremity injuries correlated significantly with total cost (r = 0.22, p = 0.001) and PTS (r = -0.25, p < 0.001) but not with the ISS. Logistic regression analysis identified runk injury, ISS and PTS as the main determinants of survival. CONCLUSIONS: The cost of pediatric trauma in Canada can be predicted from admission data and trauma scores. The cost of extremity injuries is significant and can be predicted by the PTS but not the ISS.     

Validity of applying adult TRISS analysis to injured children

Injury severity measures are becoming increasingly important for quality assurance and injury research. TRISS analysis, which uses the Revised Trauma Score (RTS) and Injury Severity Score (ISS) to predict survival, is an effective tool for comparing outcomes between trauma centers. It has been argued that blunt trauma outcome differs between children and adults, yet the Major Trauma Outcome Study (MTOS) adult data base (ages 15-54 years) regression weights have been used by others to calculate TRISS scores for injured children. This study appears to be the first to perform TRISS analysis on groups of children and adults treated by the same surgeons using the same treatment protocols to assess the validity of applying "adult" TRISS analysis to children. The charts of 346 consecutive children (ages 0-14) and 346 random adults (ages 15-54) admitted to a regional trauma center for isolated blunt trauma over a 30-month period were reviewed for demographics, mechanism of injury, RTS, ISS, and survival. Statistical evaluation included TRISS survival analysis and calculation of the Z statistic. The median ISS was 10 for both children and adults. The Z statistics for children and adults were similar (1.85 and 1.81). Analysis demonstrated the groups to be statistically identical with a nonsignificant trend toward improved survival compared with the MTOS baseline group. These data support the use of existing TRISS analysis for evaluation of pediatric trauma care.     

Prediction of outcomes in trauma: anatomic or physiologic parameters?

BACKGROUND: Prediction of outcomes after injury has traditionally incorporated measures of injury severity, but recent studies suggest that including physiologic and shock measures can improve accuracy of anatomic-based models. A recent single-institution study described a mortality predictive equation [f(x) = 3.48 - .22 (GCS) - .08 (BE) + .08 (Tx) + .05 (ISS) + .04 (Age)], where GSC is Glasgow Coma Score, BE is base excess, Tx is transfusion requirement, and ISS is Injury Severity Score, which had 63% sensitivity, 94% specificity, (receiver operating characteristic [ROC] 0.96), but did not provide comparative data for other models. We have previously documented that the Physiologic Trauma Score, including only physiologic variables (systemic inflammatory response syndrome, Glasgow Coma Score, age) also accurately predicts mortality in trauma. The objective of this study was to compare the predictive abilities of these statistical models in trauma outcomes. METHODS: Area under the ROC curve of sensitivity versus 1-specificity was used to assess predictive ability and measured discrimination of the models. RESULTS: The study cohort consisted of 15,534 trauma patients (80% blunt mechanism) admitted to a Level I trauma center over a 3-year period (mean age 37 +/- 18 years; mean Injury Severity Score 10 +/- 10; mortality 4%). Sensitivity of the new predictive model was 45%, specificity was 96%, ROC was 0.91, validating this new trauma outcomes model in our institution. This was comparable with area under the ROC for Revised Trauma Score (ROC 0.88), Trauma and Injury Severity Score (ROC 0.97), and Physiologic Trauma Score (ROC 0.95), but superior compared with admission Glasgow Coma Score (ROC 0.79), Injury Severity Score (ROC 0.79), and age (ROC 0.60). CONCLUSIONS: The predictive ability of this new model is superior to anatomic-based models such as Injury Severity Score, but comparable with other physiologic-based models such as Revised Trauma Score, Physiologic Trauma Score and Trauma, and Injury Severity Score.     

Comparison of current injury scales for survival chance estimation: an evaluation comparing the predictive performance of the ISS, NISS, and AP scores in a Dutch local trauma registration

BACKGROUND: Prediction of survival chances for trauma patients is a basic requirement for evaluation of trauma care. The current methods are the Trauma and Injury Severity Score (TRISS) and A Severity Characterization of Trauma (ASCOT). Scales for scoring injury severity are part of these methods. This study compared three injury scales, the Injury Severity Score (ISS), the New ISS (NISS), and the Anatomic Profile (AP), in three otherwise identical predictive models. METHODS: Records of the Rotterdam Trauma Center were analyzed using logistic regression. The variables used in the models were age (as a linear variable), the corrected Revised Trauma Score (RTS), a denominator for blunt or penetrating trauma, and one of the three injury scales. The original TRISS and ASCOT models also were evaluated. The resulting models were compared in terms of their discriminative power, as indicated by the receiver-operator characteristic (ROC), and calibration (Hosmer-Lemeshow [HL]) for the entire range of injury severity. RESULTS: For this study, 1,102 patients, with an average ISS of 15, met the inclusion criteria. The TRISS and ASCOT models, using original coefficients, showed excellent discriminative power (ROC, 0.94 and 0.96, respectively), but insufficient fits (HL, p = 0.001 and p = 0.03, respectively). The three fitted models also had excellent discriminative abilities (ROC, 0.95, 0.97, and 0.96, respectively). The custom ISS model was unable to fit the entire range of survival chances sufficiently (p = 0.01). Models using the NISS and AP scales provided adequate fits to the actual survival chances of the population (HL, 0.32 and 0.12, respectively). CONCLUSIONS: The AP and NISS scores particularly both managed to outperform the ISS score in correctly predicting survival chances among a Dutch trauma population. Trauma registries stratifying injuries by the ISS score should evaluate the use of the NISS and AP scores.     

Comparison of trauma assessment scores and their use in prediction of infection and death.

Current trauma assessment scores do not include an assessment of immune competence and have not been designed to predict late death from or risk of infection. We have compared the use of the Outcome Predictive Score (OPS) with other standard scales to predict clinical outcome after trauma. The OPS combines the Injury Severity Score (ISS) corrected for age (%LD50), degree of bacterial contamination, and monocyte HLA-DR antigen expression on hospital admission. The OPS was compared to the ISS, %LD50, Revised Trauma Score (RTS), Combined Trauma Score-ISS (TRISS), and Anatomical Index (AI). Sixty-one seriously ill patients were studied. Patient outcome was defined as uneventful recovery (n = 18), major infection (n = 27), and death (13 of 16 deaths resulted from infection). The assessment scores were compared for their use in prediction of these outcomes, as well as their ability to distinguish patients with good outcome from those patients who developed major infection or died, and to differentiate survival from death. Only the OPS was able to significantly segregate all five outcome groups (p less than 0.05). Although the age-adjusted ISS distinguished between survival and death (p less than 0.05), only OPS consistently distinguished between good outcome and sepsis/death (p less than 0.05), and therefore best identified the patients who developed infection. AI, RTS, and TRISS had little predictive value.     

Effect of alcohol on Glasgow Coma Scale in head-injured patients

OBJECTIVE: Almost 50% of traumatic brain-injured (TBI) patients are alcohol intoxicated. The Glasgow Coma Scale (GCS) is frequently used to direct diagnostic and therapeutic decisions in these patients. It is commonly assumed that alcohol intoxication reduces GCS, thus limiting its utility in intoxicated patients. The purpose of this study was to test the hypothesis that the presence of blood alcohol has a clinically significant impact on GCS in TBI patients. METHODS: The National Trauma Data Bank of the American College of Surgeons was queried (1994-2003). Patients 18 to 45 years of age with blunt injury mechanism, whose GCS in the emergency department, survival status, anatomic severity of TBI (Head Abbreviated Injury Score [AIS]), and blood alcohol testing status were known, were included. GCS of patients who tested positive for alcohol (n = 55,732) was compared with GCS of patients who tested negative (n = 53,197), stratified by head AIS. RESULTS: Groups were similar in age (31 +/- 8 vs. 30 +/- 8 years), Injury Severity Score (ISS; 12 +/- 11 vs. 12 +/- 11), systolic blood pressure in the ED (131 +/- 25 vs. 134 +/- 25 mm Hg), TRISS (Trauma Injury Severity Score; probability of survival (94% +/- 16% vs. 95% +/- 15%), and actual survival (96% vs. 96%). When stratified by anatomic severity of TBI, the presence of alcohol did not lower GCS by more than 1 point in any head AIS group (GCS in alcohol-positive vs. alcohol-negative patients; AIS 1 = 13.9 +/- 2.8 vs. 14.3 +/- 2.3; AIS 2 = 13.4 +/- 3.2 vs. 14.1 +/- 2.4; AIS 3 = 11.1 +/- 4.7 vs. 11.6 +/- 4.6; AIS 4 = 9.8 +/- 4.9 vs. 10.4 +/- 4.9; AIS 5 = 5.5 +/- 3.8 vs. 5.9 +/- 4.1, AIS 6: 3.4 +/- 1.1 vs. 3.8 +/- 2.8). CONCLUSION: Alcohol use does not result in a clinically significant reduction in GCS in trauma patients. Attributing low GCS to alcohol intoxication in TBI patients may delay necessary diagnostic and therapeutic interventions.     

Epidemiology and Contemporary Patterns of Trauma Deaths: Changing Place,Similar Pace,Older Face

Background The epidemiology of trauma deaths in Europe is less than well investigated. Thus, our goal was to study the contemporary patterns of trauma deaths within a defined population with an exceptionally high trauma autopsy rate. Methods This was a retrospective evaluation of 260 consecutive trauma autopsies for which we collected demographic, pre-hospital and in-hospital data. Patients were analyzed for injury severity by standard scoring systems (Abbreviated Injury Scale [AIS], Revised Trauma Score [RTS], and Injury Severity Score [ISS]), and the Trauma and Injury Severity Scale [TRISS] methodology. Results The fatal trauma incidence was 10.0 per 100,000 inhabitants (17.4 per 100,000 age-adjusted ≥ 55 years). Blunt mechanism (87%), male gender (75%), and pre-hospital deaths (52%) predominated. Median ISS was 38 (range: 4–75). Younger patients (<55 years) who died in the hospital were more often hypotensive (SBP < 90 mmHg; p = 0.001), in respiratory distress (RR < 10/min, or > 29/min; p < 0.0001), and had deranged neurology on admission (Glasgow Coma Score [GCS] ≤ 8; p < 0.0001), compared to those ≥ 55 years. Causes of death were central nervous system (CNS) injuries (67%), exsanguination (25%), and multiorgan failure (8%). The temporal death distribution is model-dependent and can be visualized in unimodal, bimodal, or trimodal patterns. Age increased (r = 0.43) and ISS decreased (r = –0.52) with longer time from injury to death (p < 0.001). Mean age of the trauma patients who died increased by almost a decade during the study period (from mean 41.7 ± 24.2 years to mean 50.5 ± 25.4 years; p = 0.04). The pre-hospital:in-hospital death ratio shifted from 1.5 to 0.75 (p < 0.007). Conclusions While pre-hospital and early deaths still predominate, an increasing proportion succumb after arrival in hospital. Focus on injury prevention is imperative, particularly for brain injuries. Although hemorrhage and multiorgan failure deaths have decreased, they do still occur. Redirected attention and focus on the geriatric trauma population is mandated.     

Helicopter scene transport of trauma patients with nonlife-threatening injuries: a meta-analysis

BACKGROUND: Helicopters have become a major part of the modern trauma care system and are frequently used to transport patients from the scene of their injury to a trauma center. While early studies reported decreased mortality for trauma patients transported by helicopters when compared with those transported by ground ambulances, more recent research has questioned the benefit of helicopter transport of trauma patients. The purpose of this study was to determine the percentage of patients transported by helicopter who have nonlife-threatening injuries. METHODS: A meta-analysis was performed on peer-review research on helicopter utilization. The inclusion criteria were all studies that evaluated trauma patients transported by helicopter from the scene of their injury to a trauma center with baseline parameters defined by Injury Severity Score (ISS), Trauma Score (TS), Revised Trauma Score (RTS), and the likelihood of survival as determined via Trauma Score-Injury Severity Score (TRISS) methodology. RESULTS: There were 22 studies comprising 37,350 patients that met the inclusion criteria. According to the ISS, 60.0% [99% confidence interval (CI): 54.5-64.8] of patients had minor injuries, According to the TS, 61.4% (99% CI: 60.8-62.0) of patients had minor injuries. According to TRISS methodology, 69.3% (99% CI: 58.5-80.2) of patients had a greater than 90% chance of survival and thus nonlife-threatening injuries. There were 25.8% (99% CI: -1.0-52.6) of patients discharged within 24 hours after arrival at the trauma center. CONCLUSIONS: The majority of trauma patients transported from the scene by helicopter have nonlife-threatening injuries. Efforts to more accurately identify those patients who would benefit most from helicopter transport from the accident scene to the trauma center are needed to reduce helicopter overutilization.