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.     

Children in Sweden admitted to intensive care after trauma

OBJECTIVE: The aims of this study were to describe the demographics, injuries, mechanisms and severity of injury, prehospital and hospital care during the first 24h, and patient outcome, in the most severely injured children cared for following trauma at a paediatric intensive care unit in Sweden. METHODS: The medical records of 131 traumatised children (0-16 years of age), admitted to the paediatric intensive care unit in Gothenburg from January 1990 to October 2000, were retrospectively examined. Nine internationally recognised scoring systems were used to calculate severity of injury, in order to predict the chances of patient survival. RESULTS: Paediatric trauma was more common in boys (68%). The mean age at injury was 7.9 years (S.D. 4.7 years). Traffic-related accidents (40%) and falls (34%) were the leading causes of injury. Injuries to the head were the most frequent, forming 24% of all injuries. Severity of injury was recorded as an Injury Severity Score median of 14, Trauma Score Injury Severity Score median of 99% and Paediatric Risk of Mortality Score median of 0.69%. The mortality rate was 3%. CONCLUSION: Trauma with admission to a paediatric intensive care unit is rare in a Swedish paediatric population. When cared for at a centre with the necessary facilities and trained personnel, these children have a good chance of survival.     

Cow-related trauma: A 10-year review of injuries admitted to a single institution

Introduction

Bovine-related injuries to farmers are common in rural communities. Many injuries are significant requiring hospital admission and surgery. We reviewed all cattle-related injuries admitted to a regional trauma centre over 10 years and detail the nature of the injuries.

Method

A retrospective review was undertaken, using hospital inpatient coding system (HIPE) to identify patients admitted following cow-related trauma for the last 10 years. From retrieved charts mechanism of injury was identified, demographics recorded and Injury Severity Score (ISS) and Trauma Injury Severity Score (TRISS) calculated based on the injuries sustained.

Results

47 patients were identified, with a median age of 53 years. 4 injuries occurred in children, and 12 in patients over 65 years old. Three-quarters of those injured were male. Kicking was the most common mechanism of injury (n = 21), but charge/head-butt injuries and trampling injuries were associated with more serious injury scores. 72% of patients were admitted under Orthopaedics as their primary care team, 25% under General Surgeons, with one patient admitted medically. Mean ISS score was 6.9 (range 1-50). 41 operative interventions were performed on 30 patients during their admission. 6.3% of patients required admission to Intensive Care with a mean length of stay of 12.3 days (range 2-21 days). There was no mortality.

Conclusion

Cow-related trauma is a common among farming communities and is a potentially serious mechanism of injury that appears to be under-reported in a hospital context. Bovine-related head-butt and trampling injuries should be considered akin to high-velocity trauma.     

Characterisation of orthopaedic trauma admitted to adult level 1 trauma centres

BACKGROUND: Despite the vast number of traumatic injuries that are orthopaedic in nature, comprehensive epidemiological data that characterise orthopaedic trauma are limited. The aim of this study was to investigate the nature of orthopaedic trauma admitted to adult Level 1 Trauma Centres. METHODS: Data were obtained from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR), which includes all patients with orthopaedic trauma admitted to the two adult Level 1 Trauma Centres in Victoria (Australia). Information was collected from the medical record and hospital databases on patients' demographics and injury event, diagnoses and management. RESULTS: Data were analysed on 784 patients recruited between August 2003 and March 2004. Patients were mainly young (<65 years) (70.7%), male (59.1%) and injured in a transport collision (51.3%). Fractures of the femur (23.7%) and spine (23.5%) were the most common injuries and were predominately managed with operative (87.6%) and conservative (78.8%) methods, respectively. Differences in most parameters were evident between younger (<65 years) and older (> or =65 years) patients. CONCLUSIONS: This study presents epidemiological data on patients with orthopaedic trauma who were admitted to adult Level 1 Trauma Centres. This information is critical for the future monitoring and evaluation of the outcomes of orthopaedic trauma.     

The Malawi trauma score: A model for predicting trauma-associated mortality in a resource-poor setting

BackgroundGlobally, traumatic injury is a leading cause of morbidity and mortality in low-income countries. Current tools for predicting trauma-associated mortality are often not applicable in low-resource environments due to a lack of diagnostic adjuncts. This study sought to derive and validate a model for predicting mortality that requires only a history and physical exam.MethodsWe conducted a retrospective analysis of all patients recorded in the Kamuzu Central Hospital trauma surveillance registry in Lilongwe, Malawi from 2011 through 2014. Using statistical randomization, 80% of patients were used for derivation and 20% were used for validation. Logistic regression modeling was used to derive factors associated with mortality and the Malawi Trauma Score (MTS) was constructed. The model fitness was tested.Results62,354 patients are included. Patients are young (mean age 23.0, SD 15.9 years) with a male preponderance (72%). Overall mortality is 1.8%. The MTS is tabulated based on initial mental status (alert, responds to voice, responds only to pain or worse), anatomical location of the most severe injury, the presence or absence of a radial pulse on examination, age, and sex. The score range is 2–32. A mental status exam of only responding to pain or worse, head injury, the absence of a radial pulse, extremes of age, and male sex all conferred a higher probability of mortality. The ROC area under the curve for the derivation cohort and validation cohort were 0.83 (95% CI 0.78, 0.87) and 0.83 (95% CI 0.75, 0.92), respectively. A MTS of 25 confers a 50% probability of death.ConclusionsThe MTS provides a reliable tool for trauma triage in sub-Saharan Africa and helps risk stratify patient populations. Unlike other models previously developed, its strength is its utility in virtually any environment, while reliably predicting injury- associated mortality.     

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.     

The injury severity score or the new injury severity score for predicting mortality, intensive care unit admission and length of hospital stay: experience from a university hospital in a developing country

INTRODUCTION: Limited research has been performed to compare the predictive abilities of the injury severity score (ISS) and the new ISS (NISS) in the developing world. PATIENTS AND METHODS: From January 2001 until January 2003 all trauma patients admitted to the American University of Beirut Medical Centre were enrolled. The statistical performance of the ISS/NISS in predicting mortality, admission to the intensive care unit (ICU) and length of hospital stay (LOS dichotomised as <10 or > or =10 days) was evaluated using receiver operating characteristic and the Hosmer-Lemeshow calibration statistic. RESULTS: A total of 891 consecutive patients were enrolled. The ISS and NISS were equivalent in predicting survival, and both performed better in patients younger than 65 years of age. However, the ISS predicted ICU admission and LOS better than the NISS. However, these predictive abilities were lower for the geriatric trauma patients aged 65 years and above compared to the other age groups. DISCUSSION: There are conflicting results in the literature about the abilities of ISS and NISS to predict mortality. However, this is the first study to report that ISS has a superior ability in predicting both LOS and ICU admission. CONCLUSION: The scoring of trauma severity may need to be individualised to different countries and trauma systems.     

Trauma care systems in India

Trauma-care systems in India are at a nascent stage of development. Industrialised cities, rural towns and villages coexist, with almost complete lack of organised trauma care. There is gross disparity between trauma services available in various parts of the country. Rural India has inefficient services for trauma care, due to the varied topography, financial constraints and lack of appropriate health infrastructure. There is no national lead agency to co-ordinate various components of a trauma system. No mechanism for accreditation of trauma centres and professionals exists. Education in trauma life-support (TLS) skills has only recently become available. A nation-wide survey encompassing various facilities has demonstrated significant deficiencies in current trauma systems.Although injury is a major public-health problem, the Government of India has failed to recognise it as a priority. Significant efforts to develop trauma-care systems across the country are seen mainly in the private sector. New initiatives under National Health Policy 2002 are expected to result in improvement in the systems, but the allocation of funds remains grossly inadequate for any significant impact on the outcome.     

The modified rapid emergency medicine score: A novel trauma triage tool to predict in-hospital mortality

BackgroundTrauma systems currently rely on imperfect and subjective tools to prioritize responses and resources, thus there is a critical need to develop a more accurate trauma severity score. Our objective was to modify the Rapid Emergency Medicine (REMS) Score for the trauma population and test its accuracy as a predictor of in-hospital mortality when compared to other currently used scores, including the Revised Trauma Score (RTS), the Injury Severity Score (ISS), the “Mechanism, Glasgow Coma Scale, Age and Arterial Pressure” (MGAP) score, and the Shock Index (SI) score.MethodsThe two-part study design involved both a modification step and a validation step. The first step incorporated a retrospective analysis of a local trauma database (3680 patients) where three components of REMS were modified to more accurately represent the trauma population. Using clinical judgment and goodness-of-fit tests, systolic blood pressure was substituted for mean arterial pressure, the weighting of age was reduced, and the weighting of Glasgow Coma Scale was increased. The second part comprised validating the new modified REMS (mREMS) score retrospectively on a U.S. National Trauma Databank (NTDB) that included 429,711 patients admitted with trauma in 2012. The discriminate power of mREMS was compared to other trauma scores using the area under the receiver operating characteristic (AUC) curve.ResultsOverall the mREMS score with an AUC of 0.967 (95% CI: 0.963–0.971) was demonstrated to be higher than RTS (AUC 0.959 [95% CI: 0.955–0.964]), ISS (AUC 0.780 [95% CI 0.770–0.791]), MGAP (AUC 0.964 [95% CI: 0.959–0.968]), and SI (AUC 0.670 [95% CI: 0.650–0.690]) in predicting in-hospital mortality on the NTDB.ConclusionIn the trauma population, mREMS is an accurate predictor of in-hospital mortality, outperforming other used scores. Simple and objective, mREMS may hold value in the pre-hospital and emergency department setting in order to guide trauma team responses.     

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.     

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.     

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.     

Revisiting the validity of APACHE II in the trauma ICU: Improved risk stratification in critically injured adults

Background

Quality and benchmarking initiatives highlight the need for accurate stratified risk adjustment. The stratification of trauma patients has relied on scores specific to trauma populations. While the Acute Physiologic and Chronic Health Evaluation (APACHE) II score has been considered “invalid” in the trauma population, we hypothesized that APAHCE II would more accurately predict outcomes in critically injured patients in whom commonly used trauma scores have inherent limitations.

Methods

A prospective cohort of critically injured patients was enrolled. Severity scores and their sub-components were collected, and in-hospital mortality was assessed. The area under the receiver operating characteristic (AUROC) curve was used to determine the predictive value of each score. Logistic regression estimated the odds of death associated with incremental changes in severity scores and their subcomponents.

Results

1019 patients were available for analysis. APACHE II was the best predictor of mortality (AUROC 0.77 versus AUROC 0.54 for ISS and 0.64 for TRISS). A unit increase in APACHE II was associated with an OR of death of 1.18 (95% CI 1.14-1.22). The components of APACHE II that contributed the most to its accuracy included temperature, serum creatinine and the Glasgow Coma Scale (GCS).

Conclusion

Critically injured patients have physiologic derangements not accurately accounted for by commonly used trauma scores. In this subset a more general ICU scoring system is useful for risk adjustment for research, administrative and quality improvement purposes.     

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.     

Improving outcomes in a regional trauma system: impact of a level III trauma center

BACKGROUND: Trauma systems decrease morbidity and mortality of injured populations, and each component contributes to the final outcome. This study evaluated the association between a referring hospital's trauma designation and the survival and resource utilization of patients transferred to a level I trauma center. METHODS: Data from the Registry of the American College of Surgeons on patients transferred to a level I trauma center during a 7-year period were subdivided into 3 categories: group 1 = level III-designated trauma center; group 2 = potential level III trauma centers; and group 3 = other transferring hospitals. Trauma and Injury Severity Score methodology was used to provide a probability estimate of survival adjusted for the effect related to injury severity, physiologic host factors, and age. A W statistic was calculated for each type of referring hospital so that comparisons between observed survival and predicted survival could be measured. Differences in W, length of stay, intensive care unit days, and ventilator days were examined using general linear models. RESULTS: Patients transferred to a level I from a level III trauma center (group 1) were more seriously injured (P < .0001) and had improved survival (P < .0018) compared with those transferred from nondesignated hospitals (groups 2 and 3). Patients transferred from large nondesignated hospitals (group 2) had outcomes similar to patients transferred from all other hospitals (group 3). Level I hospital resource utilization did not show significant differences based on referring hospital type. COMMENTS: Outcomes of patients in a trauma system are associated with trauma-center designation of the referring hospitals.     

Impact of joint theater trauma system initiatives on battlefield injury outcomes

Introduction

The US military forces developed and implemented the Joint Theater Trauma System (JTTS) and Joint Theater Trauma Registry (JTTR) using US civilian trauma system models with the intent of improving outcomes after battlefield injury.

Methods

The purpose of this analysis was to elaborate the impact of the JTTS. To quantify these achievements, the JTTR captured mechanism, acute physiology, diagnostic, therapeutic, and outcome data on 23,250 injured patients admitted to deployed US military treatment facilities from July 2003 through July 2008 for analysis. Comparative analysis to civilian trauma systems was done using the National Trauma Data Bank (NTDB).

Results

In contrast to civilian trauma systems with an 11.1% rate of penetrating injury, 68.3% of battlefield wounds were by penetrating mechanism. In the analyzed cohort, 23.3% of all patients had an Injury Severe Score (ISS) ≥16, which is similar to the civilian rate of 22.4%. In the military injury population, 66% of injuries were combat-related. In addition, in the military injury group, 21.8% had metabolic evidence of shock with a base deficit ≥5, 29.8% of patients required blood transfusion, and 6.4% of the total population of combat casualties required massive transfusion (>10 U red blood cells/24 hours). With this complex and severely injured population of battlefield injuries, the JTTS elements were used to recognize and remedy more than 60 trauma system issues requiring leadership and advocacy, education, research, and alterations in clinical care. Of particular importance to the trauma system was the implementation and tracking of performance improvement indicators and the dissemination of 27 evidence-based clinical practice guidelines (CPGs). In particular, the damage control resuscitation guideline was associated with a decrease in mortality in the massively transfused from 32% pre-CPG to 21% post-CPG. As evidence of the effectiveness of the JTTS, a mortality rate of 5.2% after battlefield hospital admission is comparable to a case fatality rate of 4.3% reported in an age-matched cohort from the NTDB.

Conclusions

JTTS initiatives contributed to improved survival after battlefield injury. The JTTS has set the standard of trauma care for the modern battlefield using contemporary systems-based methodologies.     

Predicting Survival after Trauma: a Comparison of TRISS and ASCOT in the Netherlands

Background: Evaluating the performance of a trauma system may be attempted by comparing outcome in different trauma populations. Controlling for injury severity is a necessity for such evaluations. We compare two current models for doing so: the “Trauma and Injury Severity Score” (TRISS) and “A Severity Characterization Of Trauma” (ASCOT). Material and Methods: This study of high-energy trauma victims took place in Leiden, the Netherlands, between 1993 and 1998. Using the Hosmer-Lemeshow (HL) test and receiver operator characteristic (ROC) analysis, the TRISS and ASCOT models were compared for calibration and discrimination. Results: 1,024 patients, with an average Injury Severity Score (ISS) of 13.5, were eligible for inclusion. Blunt trauma was the predominant cause of injuries. Both models gave accurate, though pessimistic, results in predicting the actual number of fatalities (n = 71). The HL test indicated a sufficient fit for the ASCOT model (p = 0.28) and an insufficient fit (p = 0.02) for TRISS. The ROC curves were nearly identical (0.97). Including age as a linear variable, instead of using the current age groups, resulted in an improved discriminative power of the models. Conclusions: The ASCOT model proved superior over TRISS in its accuracy to estimate of survival chances. This difference was most evident for victims with an estimated survival chance of 60–90%. Future national trauma researchers should therefore collect ASCOT data. Improved ASCOT models could be developed, with age as a linear variable. Received: April 25, 2002; revision accepted: September 17, 2002 Correspondence Address Prof. Arie B. van Vugt, MD, PhD, Department of General Surgery and Traumatology, Erasmus MC Rotterdam, Dr. Molewaterplein 40, Postbus 2040, 3000 CA Rotterdam, The Netherlands, Phone (+31/10) 463-5735, Fax -4757, e-mail: vanvugt@hlkd.azr.nl