The Trauma and Injury Severity Score (TRISS) revised

Background

The Trauma and Injury Severity Score (TRISS) remains the most commonly used tool for benchmarking trauma fatality outcome. Recently, it was demonstrated that the predictive power of TRISS could be substantially improved by re-classifying the component variables and treating the variable categories nominally. This study aims to develop revised TRISS models using re-classified variables, to assess these models’ predictive performances against existing TRISS models, and to identify and recommend a preferred TRISS model.

Materials and methods

Revised TRISS models for blunt and penetrating injury mechanism were developed on an adult (aged ≥15 years) sample from the National Trauma Data Bank National Sample Project (NSP), using 5-category variable classifications and weighted logistic regression. Their predictive performances were then assessed against existing TRISS models on the unweighted NSP, National Trauma Data Bank (NTDB), and New Zealand Database (NZDB) samples using area under the Receiver Operating Characteristic curve (AUC) and Bayesian Information Criterion (BIC) statistics.

Results

The weighted NSP sample included 1,124,001 adults with blunt or penetrating injury mechanism events and known discharge status, of whom 1,061,709 (94.5%) survived to discharge. Complete information for all TRISS variables was available for 896,212 (79.7%). Revised TRISS models that included main-effects and two-factor interaction terms had superior AUC and BIC statistics to main-effects models and existing TRISS models for patients with complete data in NSP, NTDB and NZDB samples. Predictive performance decreased as the number of variables with missing values included within revised TRISS models increased, but model performances generally remained superior to existing TRISS models.

Discussion

Revised TRISS models had importantly improved predictive capacities over existing TRISS models. Additionally, they were easily computed, utilised only those variables already collected for existing TRISS models, and could be applied and produce meaningful survival probabilities when one or more of the predictor variables contained missing values. The preferred revised TRISS model included main-effects and two-factor interaction terms and allowed for missing values in all predictor variables. A strong case exists for replacing existing TRISS models in trauma scoring systems benchmarking software with this preferred revised TRISS model.     

Analysis of Trauma Outcome Using the TRISS Method at a Tertiary Care Centre in Pune

Out of the various systems used to assess the outcome of polytrauma patients, trauma and injury severity score (TRISS) is considered as the standard tool for evaluating the performance of trauma centres. The present study was carried out to evaluate the outcome of severely injured patients using the TRISS method in a developing country like India and to compare it with the major trauma outcome study (MTOS). A prospective study of 300 patients of trauma was done. Outcome assessment was done for the severely injured patients using the TRISS method. Road traffic accidents (213 cases) were the most common cause of injury. Fifty-seven (19%) cases were severely injured defined as having an injury severity score ≥16. Outcome assessment was done for these patients using the TRISS method. The predicted mortality was 15.7%, while the observed mortality was 33.3%. The mean revised trauma score was 6.63 ± 1.79 and the mean injury severity score (ISS) was 23.7 ± 8.17. Compared to the MTOS, the patients in the present study had more severe injuries with higher mortality. The present method of comparison of trauma care, i.e. TRISS which uses the MTOS coefficients, does not accurately predict survival of trauma patients in the developing countries as indicated by the present and other studies. There is a need for developing a national trauma registry to derive new coefficients for trauma scoring for the Indian subcontinent so that the quality of trauma care can be compared with that in the developed countries.     

Comparison of the Trauma Outcome between Urban and Suburban Hospital

Abstract This study compared the trauma outcome between urban and suburban hospitals. The medical records of patients admitted to the intensive care unit (ICU) following trauma, obtained from 1994 to 1995 and 2002 to 2003, were examined. One was a tertiary university teaching hospital with regional emergency medical center (EMC), and the other was a small general hospital in a suburban area. Since 1999, the suburban hospital has enlarged its capacities to include EMC. In this study, the standardizing W (Ws), 95% confidence interval (CI) of Ws, and the predicted survival rate (Ps) were calculated using the Trauma and Injury Severity Score (TRISS) method. From 1994 to 1995, 225 and 121 records of the urban and suburban hospital were reviewed, respectively. The performance of trauma care in the urban hospital was more accurate than that in the suburban (95% CI of the Ws in urban and small suburban hospital: –2.30 to 2.73 and –11.40 to –5.90, respectively). The actual survival rate of the suburban hospital was significantly lower than the predicted survival rate at all revised trauma score (RTS). From 2002 to 2003, 315 and 268 medical records of urban and suburban hospital were reviewed, respectively. The 95% CI of the Ws in urban and suburban hospital was –3.56 to 0.24 and –3.73 to 0.26, respectively. In addition, there were no differences in the distribution of actual survival rate that was compared with the predicted survival rate according to injury severity score (ISS) and RTS in each hospital. After increasing the capacity of the suburban hospital, the trauma care performance was more accurate, and the ability of the physiologic support had improved. In addition, a larger suburban hospital could manage more severely injured patients without the need for transfer (mean ISS from 1994–1995 to 2002–2003: 21.0 vs. 24.3, p = 0.059, mean RTS: 7.0 and 6.2, p = 0.003; transfer:admission ratio = 0.182:0.056, respectively, p = 0.01). In conclusion, under the well-constructed emergency medical service system, the enlargement of the capacities of emergency and intensive care should improve the performance of trauma care in suburban hospital. Presented at the research forum of American College of Emergency Medicine, San Francisco, CA, USA, October 2004,     

The survival rate of patients with burns induced by explosions was significantly higher than that of common burn cases: A nationwide observational study using the Japan Trauma Data Bank

BackgroundsBlast injuries have a variety of mechanisms, with some cases resulting in immediate death and others resulting in burns as a fourth type of blast injury when the energy of the explosion is relatively low. We reported in 2020, as an incidental result, that burns caused by explosions had a higher survival rate than usual burns caused by other mechanisms. The present study confirmed whether or not burns caused by explosions had higher survival rates than those caused by other mechanisms using the Japan Trauma Data Bank (JTDB), a leading nationwide trauma registry in Japan.MethodsBurn patients registered to the JTDB database from January 2004 to March 2019 were analyzed retrospectively. The 338,744 patients registered to the JTDB database published in 2021 were identified. After exclusion, 7127 patients met the criteria for inclusion in this study. Logistic regression analyses were conducted for in-hospital survival rates using patients with burns, including cases complicated by usual trauma and burned patients without usual trauma. The survival rates by External burn grade AIS98 were compared between the explosion group and other cause groups using burn cases without usual trauma.ResultsThe cause of the explosion significantly influenced the survival according to logistic regression analyses using burn groups with and without usual trauma. For AIS 4 and 5, we found significant differences between the explosion group and other cause groups in survival rates among burn cases without usual trauma.ConclusionThe survival rate of patients with burns induced by explosions was higher than that of common burn cases according to analyses based on a burn grade of AIS98 among burn cases without common trauma. Multivariate analyses also showed that explosion burns had a significantly better outcome than those induced by other causes.     

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.     

Trauma care before and after optimisation in a level I trauma Centre: Life-saving changes

BackgroundThe implementation of trauma systems has led to a significant reduction in mortality and length of hospital stay. In our level I trauma centre, 24/7 in-hospital coverage was implemented, and a renovation of the trauma room took place to improve the trauma care. The aim of the present study was to examine the effect of the optimised in-hospital infrastructure in terms of mortality, processes and clinical outcomes.MethodsWe performed a retrospective cohort study of prospectively collected data. All adult trauma patients admitted to our trauma centre directly during two time periods (2010–2012 and 2014–2016) were included. Any patients below the age of 18 years and patients who underwent primary trauma screening in another hospital were excluded. Logistic and linear regression were used and adjusted for demographics and characteristics of trauma. The primary endpoint was mortality. The secondary endpoints were subgroups of earlier mortality rates and severely injured patients, processes and clinical outcomes.ResultsIn period I, 1290 patients were included, and in period II, 2421. The adjusted mortality in the trauma room (odds ratio (OR): 0.18; CI: 0.05–0.63) and the total in-hospital mortality (OR: 0.63 CI: 0.42–0.95) showed a significant reduction in period II. The trauma room (TR) time decreased by 30 min (p < 0.001), and the time until CT decreased by 22 min (p < 0.001). The number of delayed diagnoses and complications were significantly lower in the second period, with an OR of 0.2 (CI: 0.1–0.2) and 0.4 (CI: 0.3–0.6), respectively. The hospital length of stay and ICU length of stay decreased significantly, −1.5 day (p = 0.010) and −1.8 days (p = 0.022) respectively.ConclusionsOptimisation of the in-hospital infrastructure related to trauma care resulted in improved survival rates in both severely injured patients as well as in the whole trauma population. Moreover, the processes and clinical outcomes improved, showing a shorter hospital length of stay, shorter TR time, fewer complications and fewer delayed diagnoses.     

Applicability of the trimodal distribution of trauma deaths in a Level I trauma centre in the Netherlands with a population of mainly blunt trauma

BACKGROUND: Death due to trauma is assumed to follow a trimodal distribution. Since 1995 measures have been taken to regulate organisations involved in trauma care systems in the Netherlands. In estimating the effect of this system we have evaluated the time of death distribution in the University Medical Centre Utrecht (UMCU). STUDY DESIGN: Prospectively collected databases of all trauma victims between January 1996 and December 2005 were retrospectively reviewed. All traumatic deaths were included. Cause of death was divided into exsanguination, thorax, CNS, organ failure, pneumonia, other and unknown. RESULTS: Nine thousand eight hundred and five patients were admitted after trauma; of these patients 659 (6.7%) died. Blunt trauma occurred in 615/659 (93.3%) patients. The temporal distribution did not show a trimodal distribution. One predominant peak was observed, /=14 days, 28% and 29%, respectively. CONCLUSION: No trimodal distribution was confirmed. Only one predominant peak, with a rapid decline, was observed within the first hour after trauma. Even analysed for different causes of death, the trimodal distribution could not be demonstrated. In particular death due to CNS injury showed a complete absence of any peaks.     

Venous glucose and arterial lactate as biochemical predictors of mortality in clinically severely injured trauma patients—A comparison with ISS and TRISS

Background

Early assessment of injury severity is important in trauma. Trauma scores are calculated after the fact and are useful for audit and research, but not in the emergency clinical setting. Glucose metabolism is altered in trauma, and we hypothesised that alterations in glucose and lactate levels would be an early predictor of mortality.

Methods

Review of trauma registry data identified 1197 patients between May 2000 and September 2006 who had a trauma-team call out. Data collected included trauma scores, venous glucose (gluc), and arterial lactate (lact) on arrival. The predictive value of these variables was compared by ROC curves.

Results

The mortality rate for patients with gluc >11.0 mmol/L was 13.4% compared to 1.8% in those with gluc ≤11.0 mmol/L (p < 0.0001). Gluc had a specificity of 93.2% and a sensitivity of 37.9% for death. 13.0% of patients with lact >2.0 mmol/L died, versus 2.7% with lact ≤2.0 mmol/L, (p 0.0003, specificity 56.8% and sensitivity 81.0%). Glucose was the better biochemical predictor of mortality compared to lactate (ROC area 0.845 and 0.716, respectively). The TRISS (trauma and injury severity score) was a very accurate predictor (ROC 0.963), whereas the ISS (injury severity score) significantly less so (ROC 0.854). There was a significant correlation between gluc, ISS, and TRISS (p 0.01), as well as lactate and ISS (p 0.01).

Conclusion

Glucose and lactate can predict mortality in severe trauma. The predictive value of glucose is comparable to that of ISS, and can be more easily employed in the clinical setting.     

Performance of the modified TRISS for evaluating trauma care in subpopulations: A cohort study

IntroductionPrevious research showed that there is no agreement on a practically applicable model to use in the evaluation of trauma care. A modification of the Trauma and Injury Severity Score (modified TRISS) is used to evaluate trauma care in the Netherlands. The aim of this study was to evaluate the prognostic ability of the modified TRISS and to determine where this model needs improvement for better survival predictions.MethodsPatients were included if they were registered in the Brabant Trauma Registry from 2010 through 2015. Missing values were imputed according to multiple imputation. Subsets were created based on age, length of stay, type of injury and injury severity. Probability of survival was calculated with the modified TRISS. Discrimination was assessed with the Area Under the Receiver Operating Curve (AUROC). Calibration was studied graphically.ResultsThe AUROC was 0.84 (95% CI: 0.83, 0.85) for the total cohort (N = 69 747) but only 0.53 (95% CI: 0.51, 0.56) for elderly patients with hip fracture. Overall, calibration of the modified TRISS was adequate for the total cohort, with an overestimation for elderly patients and an underestimation for patients without brain injury.ConclusionsOutcome comparison conducted with TRISS-based predictions should be interpreted with care. If possible, future research should develop a simple prediction model that has accurate survival prediction in the aging overall trauma population (preferable with patients with hip fracture), with readily available predictors.     

The impact of diabetes on outcome in traumatically injured patients: an analysis of the National Trauma Data Bank

BACKGROUND: Studies on stress hyperglycemia in trauma patients have largely ignored diabetes, a potential confounder. The purpose of this study was to assess the relationship between diabetes and outcome in trauma patients. METHODS: Data were obtained from the National Trauma Data Bank (version 4.0). The primary outcome measures were mortality and infections. Age, injury severity, and comorbidities were analyzed as independent variables using logistic regression. RESULTS: A total of 343,250 patients were analyzed, of whom 2.7% were diabetic. On multivariate analysis, insulin-dependent diabetes was an independent although weak predictor of infectious morbidity and intensive care unit length of stay. However, diabetes was not associated with mortality or hospital length of stay. Age and injury severity were the main predictors for all outcome measures. CONCLUSIONS: Diabetes was an independent, although weak, risk factor for infectious complications in trauma patients. Age and injury severity were the most important predictors of outcome.     

A Comparison Study of the Injury Score Models

Abstract Background: A central component to the statistical analysis of trauma care is the probability of survival model, which predicts outcome of the trauma event taking into account various anatomical and physiological factors. One of the key input information to the survival model is the injury score which forms the cornerstone of trauma epidemiology. There are many scoring systems currently in use, and the Injury Severity Score (ISS) as the anatomical component of the injury in the probability of survival model is a widely used one. This paper examines the possibility of representing the anatomical component of the trauma using different injury severity scoring methods described in the literature. Material and methods: The dataset used consists of 75,371 cases from the Trauma Audit and Research Network (TARN). TARN regroups 110 hospitals in the UK and it is the largest European trauma registry. Various limitations of ISS have been described in the literature and an investigation into other scoring methods, which could be calculated from the available data, was proposed. Using the available database, the alternative injury scoring methods can be calculated and their use within a Trauma score and Injury Severity Score (TRISS) probability of survival model is assessed. Results: The current score performs reasonably well, but there is some improvement in calibration associated with introducing a score, which takes into account body-region locations of all injuries.     

The TRISS method applied to the victims of traffic accidents attended at a tertiary level emergency hospital in a developing country

In Brazil, trauma occupies third place among the various causes of death and is the first cause of death among young people. Among the various approaches to the study of trauma, analysis of the organisation and quality of care has been frequently reported in the literature. The objective of the present study was to assess the quality of care for victims of trauma due to traffic accidents provided at the Emergency Unit of the University Hospital, Faculty of Medicine of Ribeir?o Preto, SP, Brazil. The quality of care was compared between two different periods, i.e., before and after the introduction of modifications in prehospital care, and was also compared to the North American standards of the Major Trauma Outcome Study (MTOS). The Trauma Score and Injury Severity Score (TRISS) was used to calculate the probability of survival and the Z statistic was used for comparison with the MTOS. During both periods studied, the results were inferior to those obtained by the MTOS, although positive signs were detected at the Emergency Unit regarding the organisation of the system of trauma care during the study period.     

Mapping Abbreviated Injury Scale data from 1990 to 1998 versions: A stepping-stone in the contemporary evaluation of trauma

Introduction

Many trauma registries have used the 1990 revision of the Abbreviated Injury Scale (AIS; AIS90) to code injuries sustained by trauma patients. Due to changes made to the AIS codeset since its release, AIS90-coded data lacks currency in the assessment of injury severity. The ability to map between the 1998 revision of AIS (AIS98) and the current (2008) AIS version (AIS08) already exists. The development of a map for transforming AIS90-coded data into AIS98 would therefore enable contemporary injury severity estimates to be derived from AIS90-coded data.

Methods

Differences between the AIS90 and AIS98 codesets were identified, and AIS98 maps were generated for AIS90 codes which changed or were not present in AIS98. The effectiveness of this map in describing the severity of trauma using AIS90 and AIS98 was evaluated using a large state registry dataset, which coded injury data using AIS90 over several years. Changes in Injury Severity Scores (ISS) calculated using AIS90 and mapped AIS98 codesets were assessed using three distinct methods.

Results

Forty-nine codes (out of 1312) from the AIS90 codeset changed or were not present in AIS98. Twenty-four codes required the assignment of maps to AIS98 equivalents. AIS90-coded data from 78,075 trauma cases were used to evaluate the map. Agreement in calculated ISS between coded AIS90 data and mapped AIS98 data was very high (kappa = 0.971). The ISS changed in 1902 cases (2.4%), and the mean difference in ISS across all cases was 0.006 points. The number of cases classified as major trauma using AIS98 decreased by 0.8% compared with AIS90. A total of 3102 cases (4.0%) sustained at least one AIS90 injury which required mapping to AIS98.

Conclusions

This study identified the differences between the AIS90 and AIS98 codesets, and generated maps for the conversion process. In practice, the differences between AIS90- and AIS98-coded data were very small. As a result, AIS90-coded data can be mapped to the current AIS version (AIS08) via AIS98, with little apparent impact on the functional accuracy of the mapped dataset produced.     

Defining major trauma using the 2008 Abbreviated Injury Scale

BackgroundThe Injury Severity Score (ISS) is the most ubiquitous summary score derived from Abbreviated Injury Scale (AIS) data. It is frequently used to classify patients as ‘major trauma’ using a threshold of ISS >15. However, it is not known whether this is still appropriate, given the changes which have been made to the AIS codeset since this threshold was first used. This study aimed to identify appropriate ISS and New Injury Severity Score (NISS) thresholds for use with the 2008 AIS (AIS08) which predict mortality and in-hospital resource use comparably to ISS >15 using AIS98.MethodsData from 37,760 patients in a state trauma registry were retrieved and reviewed. AIS data coded using the 1998 AIS (AIS98) were mapped to AIS08. ISS and NISS were calculated, and their effects on patient classification compared. The ability of selected ISS and NISS thresholds to predict mortality or high-level in-hospital resource use (the need for ICU or urgent surgery) was assessed.ResultsAn ISS >12 using AIS08 was similar to an ISS >15 using AIS98 in terms of both the number of patients classified major trauma, and overall major trauma mortality. A 10% mortality level was only seen for ISS 25 or greater. A NISS >15 performed similarly to both of these ISS thresholds. However, the AIS08-based ISS >12 threshold correctly classified significantly more patients than a NISS >15 threshold for all three severity measures assessed.ConclusionsWhen coding injuries using AIS08, an ISS >12 appears to function similarly to an ISS >15 in AIS98 for the purposes of identifying a population with an elevated risk of death after injury. Where mortality is a primary outcome of trauma monitoring, an ISS >12 threshold could be adopted to identify major trauma patients.Level of evidenceLevel II evidence—diagnostic tests and criteria.     

Comparison of two simple models for prediction of short term mortality in patients after severe traumatic brain injury

Introduction

The subscale motor score of Glasgow Coma Scale (msGCS) and the Abbreviated Injury Score of head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim was to compare the prognostic performance of a HAIS-based prediction model including HAIS, pupil reactivity and age, and the reference prediction model including msGCS in emergency department (ED), pupil reactivity and age.

Predicting work-related disability and medical cost outcomes: A comparison of injury severity scoring methods

Introduction

Acute work-related trauma is a leading cause of death and disability among U.S. workers. Occupational health services researchers have described the pressing need to identify valid injury severity measures for purposes such as case-mix adjustment and the construction of appropriate comparison groups in programme evaluation, intervention, quality improvement, and outcome studies. The objective of this study was to compare the performance of several injury severity scores and scoring methods in the context of predicting work-related disability and medical cost outcomes.

Methods

Washington State Trauma Registry (WTR) records for injuries treated from 1998 to 2008 were linked with workers’ compensation claims. Several Abbreviated Injury Scale (AIS)-based injury severity measures (ISS, New ISS, maximum AIS) were estimated directly from ICD-9-CM codes using two software packages: (1) ICDMAP-90, and (2) Stata's user-written ICDPIC programme (ICDPIC). ICDMAP-90 and ICDPIC scores were compared with existing WTR scores using the Akaike Information Criterion, amount of variance explained, and estimated effects on outcomes. Competing risks survival analysis was used to evaluate work disability outcomes. Adjusted total medical costs were modelled using linear regression.

Results

The linked sample contained 6052 work-related injury events. There was substantial agreement between WTR scores and those estimated by ICDMAP-90 (kappa = 0.73), and between WTR scores and those estimated by ICDPIC (kappa = 0.68). Work disability and medical costs increased monotonically with injury severity, and injury severity was a significant predictor of work disability and medical cost outcomes in all models. WTR and ICDMAP-90 scores performed better with regard to predicting outcomes than did ICDPIC scores, but effect estimates were similar. Of the three severity measures, maxAIS was usually weakest, except when predicting total permanent disability.

Conclusions

Injury severity was significantly associated with work disability and medical cost outcomes for work-related injuries. Injury severity can be estimated using either ICDMAP-90 or ICDPIC when ICD-9-CM codes are available. We observed little practical difference between severity measures or scoring methods. This study demonstrated that using existing software to estimate injury severity may be useful to enhance occupational injury surveillance and research.