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.     

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.     

Prognostic value of trauma scores in pediatric patients with multiple injuries

BACKGROUND: For the quantification of multiple injuries in children, a range of different trauma scores are available, the actual prognostic value of which has, however, not so far been investigated and compared in a group of patients. METHODS: In 261 polytraumatized children and adolescents, 11 trauma scores (Abbreviated Injury Scale [AIS], Injury Severity Score [ISS], Glasgow Coma Scale [GCS], Acute Trauma Index [ATI], Shock Index [SI], Trauma Score [TS], Revised Trauma Score [RTS], Modified Injury Severity Score [MISS], Trauma and Injury Severity Score [TRISS]-Scan, Hannover Polytrauma Score [HPTS], and Pediatric Trauma Score [PTS]) were calculated, and their prognostic relevance in terms of survival, duration of intensive care treatment, hospital stay, and long-term outcome analyzed. RESULTS: With a specificity of 80%, physiologic scores (TS, RTS, GCS, ATI) showed a greater accuracy (79-86% vs. 73-79%) with regard to survival prediction than did the anatomic scores (AIS, HPTS, ISS, PTS); combined forms of these two types of score (TRISS-Scan, MISS) did not provide any additional information (76-80%). Overall, the TRISS-Scan was the score that showed the highest correlation with duration of treatment and long-term outcome. Trauma scores specially conceived for use with children (PTS, MISS) failed to show any superiority vis-à-vis trauma scores in general. CONCLUSION: With regard to prognostic quality and ease of use in the practical setting, TS and the TRISS-Scan are recommended for polytrauma in children and adolescents. Special pediatric scores are not necessary.     

Direct transport to the operating room for resuscitation of trauma patients

Two hundred forty trauma patients were transported directly from the scene to a specially designed operating room (OR) for resuscitation, bypassing the Emergency Department (ED). Triage criteria included a systolic BP less than or equal to 80 mm Hg, penetrating torso trauma, multiple long-bone fractures, major limb amputation, extensive soft-tissue wounds, severe maxillofacial hemorrhage, and witnessed arrest (WA). The mechanism of injury, transport mode, age, sex, admitting Revised Trauma Score (RTS), Injury Severity Score (ISS), Abbreviated Injury Scale (AIS), operative procedures, and outcome were recorded. Utilizing the current weights from the Major Trauma Outcome Study, the predicted survival (TRISS) of the total group and of several subgroups was compared to the observed survival. The mean ISS was 29.3. The survival rate for the total group was 70.4%. For the 58.7% who required major operative intervention, the mean time of OR arrival to anesthesia induction was 8.5 minutes. Non-arrested, hypotensive blunt trauma victims requiring therapeutic laparotomy had a higher than predicted survival observed survival = 0.75 versus average TRISS = 0.55; p less than 0.0002) and therefore appeared to benefit from this technique. Patients suffering witnessed arrest in the field did not benefit.     

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.     

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)     

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.     

A Comparison of the Kampala Trauma Score (KTS) with the Revised Trauma Score (RTS), Injury Severity Score (ISS) and the TRISS Method in a Ugandan Trauma Registry

Abstract Background: The public health significance of injuries that occur in developing countries is now recognized. In 1996, as part of the injury surveillance registry in Kampala, Uganda, a new score, the Kampala Trauma Score (KTS) was instituted. The KTS, developed in light of the limited resource base of sub-Saharan Africa, is a simplified composite of the Revised Trauma Score (RTS) and the Injury Severity Score (ISS) and closely resembles the Trauma Score and Injury Severity Score (TRISS). Patients and Methods: The KTS was applied retrospectively to a cohort of prospectively accrued urban trauma patients with the RTS, ISS and TRISS calculated. Using ROC (receiver operating characteristics) analysis, logistic regression models and sensitivity and specificity cutoff analysis, the KTS was compared to these three scores. Results: Using logistic regression models and areas under the ROC curve, the RTS proved a more robust predictor of death at 2 weeks in comparison to the KTS. However, differences in screening performance were marginal (areas under the ROC curves were 87% for the RTS and 84% for the KTS) with statistical significance only reached for an improved specificity (67% vs. 47%; p < 0.001), at a fixed sensitivity of 90%. In addition, the KTS predicted hospitalization at 2 weeks more accurately. Conclusion: The KTS statistically performs comparably to the RTS and ISS alone as well as to the TRISS but has the added advantage of utility. Therefore, the KTS has potential as a triage tool in resource-poor and similar health care settings.     

Is outcome worse in a small volume Canadian trauma centre?

The minimum number of seriously injured patients required to maintain clinical competence and achieve acceptable clinical competence in a single trauma centre is unknown. It has been suggested that the probability of survival is improved in hospitals treating greater than 200 trauma patients annually. We sought to determine if probability of survival was lower in our small volume centre. Between 1986 and 1989, 752 (522 male, 230 female; average age, 36 years) trauma patients were admitted to our institution. The major mechanism of injury was blunt (89%). All patients underwent trauma severity scoring. Trauma Score, Injury Severity Score, and a Revised Trauma Score were used to derived the probability of survival by the TRISS method. The mean Injury Severity Score was 23.3 and the mean Trauma Score was 13.2. The overall mortality rate was 15.8%. The Z statistic demonstrated no significant difference between actual and predicted deaths for the 4-year period or for any individual year (range, -1.05 to 1.26, p greater than 0.05). The M statistic was 0.753. We conclude that, despite fewer trauma patient admissions (less than 200 per year), comparable clinical results can be achieved by surgeons dedicated to trauma management.     

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).     

Impact of cirrhosis on outcomes in trauma

BACKGROUND: Cirrhosis as an independent predictor of poor outcomes in trauma patients was identified in 1990. We hypothesized that the degree of preinjury hepatic dysfunction is, by itself, an independent predictor of mortality. STUDY DESIGN: The trauma registry at our Level I trauma center was queried for all ICD-9 codes for liver disease from 1999 to 2003, and patients were categorized as having Child-Turcotte-Pugh (CTP) class A, B, or C cirrhosis. Data analyzed included age, mechanism of injury, Abbreviated Injury Score (AIS), Injury Severity Score (ISS), Glasgow Coma Score (GCS), hospital length of stay, ventilator days, procedures performed, transfusion of blood products, admission lactate, base deficit, and mortality. Trauma Related Injury Severity Score (TRISS) methodology was used to calculate the probability of survival. Outcomes data were analyzed, and statistical comparison was performed using group t-test. RESULTS: Of the 50 patients meeting study criteria, 31 had alcohol-related cirrhosis, 18 had a history of hepatitis C, and 1 had cryptogenic cirrhosis. Twenty (40%) met CTP A classification, 16 (32%) met CTP B criteria, and 14 (28%) had CTP class C cirrhosis. One death occurred in the CTP A and B groups. Comparison between the five survivors and nine nonsurvivors from CTP class C showed no statistical significance in terms of age, ISS, TRISS, or GCS. CONCLUSIONS: The mortality rate for class C cirrhotic patients posttrauma continues to be higher than that predicted by TRISS, although patients with less severe hepatic dysfunction do not appear to have significantly lower than predicted survival. The degree of hepatic dysfunction remains an independent predictor of mortality and CTP C criteria must be considered when determining outcomes for patients posttrauma.     

Exploring injury severity measures and in-hospital mortality: A multi-hospital study in Kenya

IntroductionLow- and middle-income countries (LMICs) have a disproportionately high burden of injuries. Most injury severity measures were developed in high-income settings and there have been limited studies on their application and validity in low-resource settings. In this study, we compared the performance of seven injury severity measures: estimated Injury Severity Score (eISS), Glasgow Coma Score (GCS), Mechanism, GCS, Age, Pressure score (MGAP), GCS, Age, Pressure score (GAP), Revised Trauma Score (RTS), Trauma and Injury Severity Score (TRISS) and Kampala Trauma Score (KTS), in predicting in-hospital mortality in a multi-hospital cohort of adult patients in Kenya.MethodsThis study was performed using data from trauma registries implemented in four public hospitals in Kenya. Estimated ISS, MGAP, GAP, RTS, TRISS and KTS were computed according to algorithms described in the literature. All seven measures were compared for discrimination by computing area under curve (AUC) for the receiver operating characteristics (ROC), model fit information using Akaike information criterion (AIC), and model calibration curves. Sensitivity analysis was conducted to include all trauma patients during the study period who had missing information on any of the injury severity measure(s) through multiple imputations.ResultsA total of 16,548 patients were included in the study. Complete data analysis included 14,762 (90.2%) patients for the seven injury severity measures. TRISS (complete case AUC: 0.889, 95% CI: 0.866–0.907) and KTS (complete case AUC: 0.873, 95% CI: 0.852–0.892) demonstrated similarly better discrimination measured by AUC on in-hospital deaths overall in both complete case analysis and multiple imputations. Estimated ISS had lower AUC (0.764, 95% CI: 0.736–0.787) than some injury severity measures. Calibration plots showed eISS and RTS had lower calibration than models from other injury severity measures.ConclusionsThis multi-hospital study in Kenya found statistical significant higher performance of KTS and TRISS than other injury severity measures. The KTS, is however, an easier score to compute as compared to the TRISS and has stable good performance across several hospital settings and robust to missing values. It is therefore a practical and robust option for use in low-resource settings, and is applicable to settings similar to Kenya.     

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.     

Measuring trauma outcomes in India: an analysis based on TRISS methodology in a Mumbai university hospital

BACKGROUND: In this prospective study, the TRISS methodology is used to compare trauma care at a university hospital (Lokmanya Tilak Municipal General (LTMG) Hospital) in Mumbai, India, with the standards reported in the Major Trauma Outcome Study (MTOS). METHODS: Between 1 August 2001 and 31 May 2002, 1074 severely injured patients were included in the study. Survival analysis was completed for 98.3% of the patients. RESULTS: The majority of the patients were men (84%) and the average age was 31 years. 90.4% were blunt injuries, with road traffic crashes (39.2%) being the most common cause. The predicted mortality was 10.89% and the observed mortality was 21.26%. The mean Revised Trauma Score (RTS) was 6.61 +/- 1.65 and the mean Injury Severity Score (ISS) was 16.7 +/- 10.67. The average probability of survival (Ps) was 89.14. The M and Z statistics were 0.84 and -14.1593, respectively. CONCLUSION: The injured in India were found to be older, the injuries more severe and with poorer outcomes, than in the MTOS study.     

Clinical retrospective and comparative study on diaphragm injuries in 46 cases

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Revision of TRISS for intubated patients.

The TRISS system is an important, widely used method for predicting survival in trauma patients. One significant shortcoming of TRISS is its inability to include intubated patients in survival analysis because a respiratory rate and a verbal response are not obtainable. This report describes one approach to this problem. Data from 994 patients with blunt trauma were examined. Like TRISS, survival probability was calculated using a logistic regression model that included age and Injury Severity Score (ISS); however, the best motor response and systolic blood pressure were used in place of the Revised Trauma Score (RTS). With this model, the sensitivity, specificity, and misclassification rate were 57%, 98.9%, and 3.6%, respectively. For TRISS, the sensitivity, specificity, and misclassification rate are 58.8%, 99.3%, and 3.0%, respectively. Thus, our model has predictive performance comparable with TRISS. More importantly, it is applicable to intubated patients who are not pharmacologically paralyzed. Further investigation with larger data bases is necessary.     

Predicting trauma patient mortality: ICD [or ICD-10-AM] versus AIS based approaches

Background: The International Classification of Diseases Injury Severity Score (ICISS) has been proposed as an International Classification of Diseases (ICD)‐10‐based alternative to mortality prediction tools that use Abbreviated Injury Scale (AIS) data, including the Trauma and Injury Severity Score (TRISS). To date, studies have not examined the performance of ICISS using Australian trauma registry data. This study aimed to compare the performance of ICISS with other mortality prediction tools in an Australian trauma registry. Methods: This was a retrospective review of prospectively collected data from the Victorian State Trauma Registry. A training dataset was created for model development and a validation dataset for evaluation. The multiplicative ICISS model was compared with a worst injury ICISS approach, Victorian TRISS (V‐TRISS, using local coefficients), maximum AIS severity and a multivariable model including ICD‐10‐AM codes as predictors. Models were investigated for discrimination (C‐statistic) and calibration (Hosmer–Lemeshow statistic). Results: The multivariable approach had the highest level of discrimination (C‐statistic 0.90) and calibration (H–L 7.65, P= 0.468). Worst injury ICISS, V‐TRISS and maximum AIS had similar performance. The multiplicative ICISS produced the lowest level of discrimination (C‐statistic 0.80) and poorest calibration (H–L 50.23, P < 0.001). Conclusions: The performance of ICISS may be affected by the data used to develop estimates, the ICD version employed, the methods for deriving estimates and the inclusion of covariates. In this analysis, a multivariable approach using ICD‐10‐AM codes was the best‐performing method. A multivariable ICISS approach may therefore be a useful alternative to AIS‐based methods and may have comparable predictive performance to locally derived TRISS models.     

Sudden survival improvement in critical neurotrauma: An exploratory analysis using a stratified statistical process control technique

BackgroundOutcome after trauma depends on patient characteristics, quality of care, and random events. The TRISS model predicts probability of survival (Ps) adjusted for Injury Severity Score (ISS), Revised Trauma Score (RTS), mechanism of injury, and age. Quality of care is often evaluated by calculating the number of “excess” survivors, year by year. In contrast, the Variable Life-Adjusted Display (VLAD) technique allows rapid detection of altered survival. VLAD adjusts each death or survival by the patient's risk status and graphically displays accumulated number of unexpected survivors over time. We evaluated outcome changes and their time relation to trauma service improvements.MethodsObservational, retrospective study of the total 2001–2011 trauma population from a Level I trauma centre. Outcome was 30-day survival. Ps was calculated with the TRISS model, 2005 coefficients. VLAD graphs were created for the entire population and for subpopulations stratified by ISS level, ISS body region (Head/Neck, Face, Chest, Abdomen/Pelvic contents, Extremities/Pelvic girdle, External), and maximum Abbreviated Injury Scale (maxAIS) score in each region. Piecewise linear regression identified VLAD graph breakpoints.Results12,191 consecutive trauma patients (median age 35 years, 72% males, 91% blunt injury, 41% ISS ≥ 16) formed the dataset. Their VLAD graph indicated performance equal to TRISS predicted survival until a sudden improvement in late 2004. From then survival remained improved but unchanged through 2011. Total number of excess survivors was 141. Inspection of subgroup VLAD graphs showed that the increased survival mainly occurred in patients having at least one Head/Neck AIS 5 injury. The effect was present in both isolated and multitraumatised maxAIS 5 Head/Neck trauma. The remaining trauma population showed unchanged survival, superior to TRISS predicted, throughout the study period.Important general and neurotrauma-targeted improvements in our trauma service could underlie our findings: A formalised trauma service, damage control resuscitation protocols, structured training, increased helicopter transfer capacity, consultant-based neurosurgical assessment, a doubling of emergency neurosurgical procedures, and improved neurointensive care.ConclusionsStratified VLAD enables continuous, high-resolution system analysis. We encourage trauma centres to explore their data and to monitor future system changes.