Limitations of the TRISS method for interhospital comparisons: a multihospital study

Comparing NEWS2, TRISS, and RTS in predicting mortality rate in trauma patients based on prehospital data set: a diagnostic study

BACKGROUND

In the recent years, National Early Warning Score2 (NEWS2) is utilized to predict early on, the worsening of clinical status in patients. To this date the predictive accuracy of National Early Warning Score (NEWS2), Revised Trauma Score (RTS), and Trauma and injury severity score (TRISS) regarding the trauma patients' mortality rate have not been compared. Therefore, the objective of this study is comparing NEWS2, TRISS, and RTS in predicting mortality rate in trauma patients based on prehospital data set.

METHODS

This cross-sectional retrospective diagnostic study performed on 6905 trauma patients, of which 4191 were found eligible, referred to the largest trauma center in southern Iran, Shiraz, during 2022-2023 based on their prehospital data set in order to compare the prognostic power of NEWS2, RTS, and TRISS in predicting in-hospital mortality rate. Patients are divided into deceased and survived groups. Demographic data, vital signs, and GCS were obtained from the patients and scoring systems were calculated and compared between the two groups. TRISS and ISS are calculated with in-hospital data set; others are based on prehospital data set.

RESULTS

A total of 129 patients have deceased. Age, cause of injury, length of hospital stay, SBP, RR, HR, temperature, SpO2, and GCS were associated with mortality (p-value < 0.001). TRISS and RTS had the highest sensitivity and specificity respectively (77.52, CI 95% [69.3-84.4] and 93.99, CI 95% [93.2-94.7]). TRISS had the highest area under the ROC curve (0.934) followed by NEWS2 (0.879), GCS (0.815), RTS (0.812), and ISS (0.774). TRISS and NEWS were superior to RTS, GCS, and ISS (p-value < 0.0001).

CONCLUSION

This novel study compares the accuracy of NEWS2, TRISS, and RTS scoring systems in predicting mortality rate based on prehospital data. The findings suggest that all the scoring systems can predict mortality, with TRISS being the most accurate of them, followed by NEWS2. Considering the time consumption and ease of use, NEWS2 seems to be accurate and quick in predicting mortality based on prehospital data set.

Use of the Trauma and Injury Severity Score (TRISS) as a Predictor of Patient Outcome in Cases of Trauma Presenting in the Trauma and Emergency Department of a Tertiary Care Institute

BACKGROUND

In this study, we used the anatomic scoring system Abbreviated Injury Scale (AIS) to calculate the Injury Severity Score (ISS) and the physiological scoring system for the Revised Trauma Score (RTS) on the arrival of patients. Both scores were used to calculate the Trauma and Injury Severity Score (TRISS) for predicting the patient outcome in a case of trauma.

METHODS

This prospective, cross-sectional, observational study was carried out at the trauma centre of a tertiary care institute and included patients of either sex, age ≥18 years, and ISS ≥15. A total of 2084 cases of trauma over a period of 18 months were assessed, and 96 cases of blunt trauma meeting the inclusion criteria were studied.

RESULTS

Patients injured in road traffic accidents constituted the maximum caseload. Out of a sample size of 96 patients with ISS ≥15, 77 died during the treatment and 19 survived. The ISS ranged from 15 to 66, with a mean ± SD score of 27.48 ± 8.79. Non-survivors had a statistically higher significant ISS than survivors (p<0.001). The RTS ranged from <1 to 7.84, with a mean ± SD score of 4.52 ± 2.08. Non-survivors had low RTS (RTS <5, n=52) compared to survivors, and the difference was statistically significant (p<0.001). The mean ± SD TRISS (Ps) score was 0.69 ± 2.288. In the non-survivor (NS) group, 15 patients had TRISS (Ps) between 0.26-0.50, followed by 0.51-0.75 (n=18), 0.76-0.90 (n=12), and 0.90-0.95 (n=11). While 16 survivors had TRISS (Ps) between 0.96 and 1, a statistically significant association was found between TRISS and patient outcome (p-value <0.001). On the receiver operating characteristic (ROC) curve analysis, the sensitivity of TRISS (94.7%) and RTS was found to be comparable (94.7%), whereas ISS was less sensitive (36.8%) in predicting the patient outcome. RTS (79.2%) and TRISS (76.6%) scores were more specific than ISS (5.2%) for outcome analysis.

CONCLUSION

The TRISS score is useful in the management of trauma patients as it can satisfactorily predict mortality in a case of trauma. The trauma scores are of immense help in determining the nature of injury in medicolegal cases.

Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury

Traumatic brain injury (TBI) occurs frequently, and acute TBI requiring surgical treatment is closely related to patient survival. Models for predicting the prognosis of patients with TBI do not consider various factors of patient status; therefore, it is difficult to predict the prognosis more accurately. In this study, we created a model that can predict the survival of patients with TBI by adding hematologic parameters along with existing non-hematologic parameters. The best-fitting model was created using the Akaike information criterion (AIC), and hematologic factors including preoperative hematocrit, preoperative C-reactive protein (CRP), postoperative white blood cell (WBC) count, and postoperative hemoglobin were selected to predict the prognosis. Among several prediction models, the model that included age, Glasgow Coma Scale, Injury Severity Score, preoperative hematocrit, preoperative CRP, postoperative WBC count, postoperative hemoglobin, and postoperative CRP showed the highest area under the curve and the lowest corrected AIC for a finite sample size. Our study showed a new prediction model for mortality in patients with TBI using non-hematologic and hematologic parameters. This prediction model could be useful for the management of patients with TBI.

RISC II is superior to TRISS in predicting 30-day mortality in blunt major trauma patients in Hong Kong

PURPOSE

Hong Kong (HK) trauma registries have been using the Trauma and Injury Severity Score (TRISS) for audit and benchmarking since their introduction in 2000. We compare the mortality prediction model using TRISS and Revised Injury Severity Classification, version II (RISC II) for trauma centre patients in HK.

METHODS

This was a retrospective cohort study with all five trauma centres in HK. Adult trauma patients with Injury Severity Score (ISS) > 15 suffering from blunt injuries from January 2013 to December 2015 were included. TRISS models using the US and local coefficients were compared with the RISC II model. The primary outcome was 30-day mortality and the area under the receiver operating characteristic curve (AUC) for tested models.

RESULTS

1840 patients were included, of whom 1236/1840 (67%) were male. Median age was 59 years and median ISS was 25. Low falls were the most common mechanism of injury. The 30-day mortality was 23%. RISC II yielded a superior AUC of 0.896, compared with the TRISS models (MTOS: 0.848; PATOS: 0.839; HK: 0.858). Prespecified subgroup analyses showed that all the models performed worse for age ≥ 70, ASA ≥ III, and low falls. RISC II had a higher AUC compared with the TRISS models in all subgroups, although not statistically significant.

CONCLUSION

RISC II was superior to TRISS in predicting the 30-day mortality for Hong Kong adult blunt major trauma patients. RISC II may be useful when performing future audit or benchmarking exercises for trauma in Hong Kong.

Evaluating trauma scoring systems for patients presenting with gunshot injuries to a district-level urban public hospital in Cape Town, South Africa

Introduction

Trauma scoring systems are widely used in emergency settings to guide clinical decisions and to predict mortality. It remains unclear which system is most suitable to use for patients with gunshot injuries at district-level hospitals. This study compares the Triage Early Warning Score (TEWS), Injury Severity Score (ISS), Trauma and Injury Severity Score (TRISS), Kampala Trauma Score (KTS) and Revised Trauma Score (RTS) as predictors of mortality among patients with gunshot injuries at a district-level urban public hospital in Cape Town, South Africa.

Methods

Gunshot-related patients admitted to the resuscitation area of Khayelitsha Hospital between 1 January 2016 and 31 December 2017 were retrospectively analysed. Receiver Operating Characteristic (ROC) analysis were used to determine the accuracy of each score to predict all-cause in-hospital mortality. The odds ratio (with 95% confidence intervals) was used as a measure of association.

Results

In total, 331 patients were included in analysing the different scores (abstracted from database n = 431, excluded: missing files n = 16, non gunshot injury n = 10, <14 years n = 1, information incomplete to calculate scores n = 73). The mortality rate was 6% (n = 20). The TRISS and KTS had the highest area under the ROC curve (AUC), 0.90 (95% CI 0.83-0.96) and 0.86 (95% CI 0.79–0.94), respectively. The KTS had the highest sensitivity (90%, 95% CI 68-99%), while the TEWS and RTS had the highest specificity (91%, 95% CI 87–94% each).

Conclusions

None of the different scoring systems performed better in predicting mortality in this high-trauma burden area. The results are limited by the low number of recorded deaths and further studies are needed.

•

Gunshot injuries most often occurs in young males.

•

Trauma scores can be used to prognosticate patients in order to allocate appropriate resources.

•

Accuracy-related data of trauma scores in entry-level hospitals is limited.

Validation of the Norwegian survival prediction model in trauma (NORMIT) in Swedish trauma populations

BACKGROUND

Trauma survival prediction models can be used for quality assessment in trauma populations. The Norwegian survival prediction model in trauma (NORMIT) has been updated recently and validated internally (NORMIT 2). The aim of this observational study was to compare the accuracy of NORMIT 1 and 2 in two Swedish trauma populations.

METHODS

Adult patients registered in the national trauma registry during 2014-2016 were eligible for inclusion. The study populations comprised the total national trauma (NT) population, and a subpopulation of patients admitted to a single level I trauma centre (TC). The primary outcome was 30-day mortality. Model validation included receiver operating characteristic (ROC) curve analysis and GiViTI calibration belts. The calibration was also assessed in subgroups of severely injured patients (New Injury Severity Score (NISS) over 15).

RESULTS

A total of 26 504 patients were included. Some 18·7 per cent of patients in the NT population and 2·6 per cent in the TC subpopulation were excluded owing to missing data, leaving 21 554 and 3972 respectively for analysis. NORMIT 1 and 2 showed excellent ability to distinguish between survivors and non-survivors in both populations, but poor agreement between predicted and observed outcome in the NT population with overestimation of survival, including in the subgroup with NISS over 15. In the TC subpopulation, NORMIT 1 underestimated survival irrespective of injury severity, but NORMIT 2 showed good calibration both in the total subpopulation and the subgroup with NISS over 15.

CONCLUSION

NORMIT 2 is well suited to predict survival in a Swedish trauma centre population, irrespective of injury severity. Both NORMIT 1 and 2 performed poorly in a more heterogeneous national population of injured patients.

Hospital readmissions in paediatric trauma patients: A 10-year Australian review

AIM

Readmission of paediatric trauma patients is associated with increased hospital length of stay, additional operative procedures and significant costs to the health-care system. The rates and causes of readmission of paediatric trauma patients are not well reported outside of the USA or single centres. This nation-wide study is the first in Australia to examine the readmission rates, costs and characteristics of Australian paediatric trauma patients.

METHODS

This was a retrospective examination of linked hospitalisation and mortality data for injured children aged 16 or younger from 1 July 2001 to 30 June 2012, readmitted to hospital within 28 days of discharge. Data including injury severity, nature of injury, episodes of care and costs were extracted from hospitalisation data.

RESULTS

There were 37 603 injury children aged ≤16 years readmitted to hospital within 28 days during the 10-year period, a readmission rate of 5.5%. The most common principal injury requiring readmission was fracture (52.6%) and burns (19.3%). A total of 66% of all patients had a readmission diagnosis of injury, complication of their initial injury or complication of surgical and medical care; 30% were readmitted for a specific procedure or follow-up care. The total cost of readmissions was AU$108 million.

CONCLUSIONS

Hospital readmission rates of paediatric trauma patients in Australia are due to injury or a complication of injury and are associated with significant costs. Early identification of at-risk patients and the prevention of complications are needed to prevent the ongoing burden of readmission.

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

INTRODUCTION

Previous 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.

METHODS

Patients 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.

RESULTS

The 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.

CONCLUSIONS

Outcome 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.

Analysis of preventable deaths and errors in trauma care in a Scandinavian trauma level-I centre

BACKGROUND

The wide disparity in the methodology of preventable death analysis has created a lack of comparability among previous studies. The guidelines for the peer review (PR) procedure suggest the inclusion of risk-adjustment methods to identify patients to review, that is, exclude non-preventable deaths (probability of survival [Ps] < 25%) or focus on preventable deaths (Ps > 50%). We aimed to, through PR process, (1) identify preventable death and errors committed in a level-I trauma centre, and (2) explore the use of different risk-adjustment methods as a complement.

METHODS

A multidisciplinary committee reviewed all trauma patients, which died a trauma-related death, within 30 days of admission to Karolinska University Hospital, Stockholm, in the period of 2012-2016. Ps was calculated according to TRISS and NORMIT and their accuracy where compared.

RESULTS

Two hundred and ninety-eight deaths were identified and 252 were reviewed. The majority of deaths occurred between 1 and 7 days. Ten deaths (4.0%) were classified as preventable. Sixty-seven errors were identified in 53 (21.0%) deaths. The most common error was inappropriate treatment in all deaths (21 of 67) and in preventable deaths (5 of 13). Median Ps in non-preventable deaths was higher than the cut-off (<25%) and Ps-TRISS was almost twice as high as Ps-NORMIT (65% vs 33%, P < .001). Two clinically judged preventable deaths with Ps <25% would have been missed with both models. Median Ps in preventable deaths was above the cut-off (>50%) and higher with Ps-TRISS vs Ps-NORMIT (75% vs 58%, P < .001). Three and 4 clinically judged preventable deaths would have been missed, respectively, for TRISS and NORMIT, if using this cut-off.

CONCLUSION

Preventable deaths were commonly caused by clinical judgment errors in the early phases but death occurred late. Ps calculated with NORMIT was more accurate than TRISS in predicting mortality, but both perform poorly in identifying preventable and non-preventable deaths when applying the cut-offs. PR of all trauma death is still the golden standard in preventability analysis.

Risk stratification tools in emergency general surgery

The use of risk stratification tools (RST) aids in clinical triage, decision making and quality assessment in a wide variety of medical fields. Although emergency general surgery (EGS) is characterized by a comorbid, physiologically acute patient population with disparately high rates of perioperative morbidity and mortality, few RST have been explicitly examined in this setting. We examined the available RST with the intent of identifying a tool that comprehensively reflects an EGS patients perioperative risk for death or complication. The ideal tool would combine individualized assessment with relative ease of use. Trauma Scoring Systems, Critical Care Scoring Systems, Surgical Scoring Systems and Track and Trigger Models are reviewed here, with the conclusion that Emergency Surgery Acuity Score and the American College of Surgeons National Surgical Quality Improvement Programme Universal Surgical Risk Calculator are the most applicable and appropriate for EGS.

Clinical Outcomes of Trauma Patients after Implementation of a Standardised Diversion Protocol for Trauma Patients in Two Regional Hospitals in Hong Kong

Introduction

Despite recent advance in prehospital trauma diversion, patients are triaged to the nearest medical facility before transferred to designated trauma centre. A new standardised diversion protocol for trauma patients was implemented on 1st April 2011 to facilitate trauma care. Severely-injured patients were transferred to designated trauma centre directly from emergency department of the regional hospital after initial resuscitation.

Objective

This study was undertaken to examine clinical outcomes of trauma patients after implementation of the new standardised diversion protocol for trauma patients in the emergency department.

Method

This was a before-and-after interventional study on trauma patients presenting to the emergency department in critical or emergency conditions during the study period from 1st April 2011 to 31st March 2012. Patients presented in the two-year period before implementation of the trauma protocol were used as historical control. Medical records of eligible cases were reviewed. Main outcome measures were 30-day mortality, length of hospital stay and time to definitive care. Mortality data was compared with oversea standard by TRISS methodology.

Results

There were 153 eligible patients in the study group and 355 in the historical control group. After new arrangement of trauma diversion, W-statistics improves from -1.26 to 0.09. Z-statistics was -2.03 before and 0.09 after implementation. M-statistics were 0.91 before and 0.88 after the new protocol. Mean time to definitive care was shortened by 33.4 minutes in the subgroup who were transferred to trauma centre after trauma team activation (p=0.005).

Conclusion

A trend of improved outcomes and shorter time to definitive care are observed after implementation of the new trauma diversion protocol. (Hong Kong j.emerg.med. 2015;22:201-209)

Preinjury ASA score as an independent predictor of readmission after major traumatic injury

Background

Patients with trauma have a high predisposition for readmission after discharge. Unplanned solicitation of medical services is a validated quality of care indicator and is associated with considerable economic costs. While the existing literature emphasizes the severity of the injury, there is heterogeneity in defining preinjury health status. We evaluate the validity of the American Society of Anesthesiologists (ASA) Physical Status score as an independent predictor of readmission and compare it to the Charlson Comorbidity Index (CCI).

Methods

This is a single center, retrospective cohort study based on adult patients (>18 years of age) with trauma admitted to the Ottawa Hospital from January 1, 2004 to November 1, 2014. A multivariate logistic regression model is used to control for confounding and assess individual predictors. Outcome is readmission to hospital within 30 days, 3 months and 6 months.

Results

A total of 4732 adult patients were included in this analysis. Readmission rates were 6.5%, 9.6% and 11.8% for 30 days, 3 months and 6 months, respectively. Higher preinjury ASA scores demonstrated significantly increased risk of readmission across all levels in a dose-dependent manner for all time frames. The effect of preinjury ASA scores on readmission is most striking at 30 days, with patients demonstrating a 2.81 (1.88–4.22, P<0.0001), 3.59 (2.43–5.32, P<0.0001) and 7.52 (4.72–11.99, P<0.0001) fold odds of readmission for ASA class 2, 3 and 4, respectively, as compared with healthy ASA class 1 patients. The ASA scores outperformed the CCI at 30 days and 3 months.

Conclusions

The preinjury ASA score is a strong independent predictor of readmission after traumatic injury. In comparison to the CCI, the preinjury ASA score was a better predictor of readmission at 3 and 6 months after a major traumatic injury.

Level of Evidence

Prognostic and Epidemiological Study, Level III.

Evolving Challenges in Prehospital Trauma Services: Current Issues and Suggested Evaluation Tools

For the past two decades, prehospital trauma care has been addressed almost generically in terms of the related approaches to epidemiology, research, and management. However, evolving directions in research have helped emergency medical services (EMS) practitioners to delineate more focused treatment strategies according to the mechanism of injury, anatomic involvement, and the patient's clinical condition. Recent studies in the areas of trauma-associated circulatory arrest, severe blunt head injury, and post-traumatic hemorrhage following penetrating truncal injury suggest that current standard approaches to patient care should be reconsidered. In turn, this need for re-examination of trauma management strategies calls for the development of appropriate evaluation tools within EMS systems. Proper research design is dependent upon several key issues including: 1) the type of study (system study versus examination of a specific intervention); 2), the population under study; 3) physiological and anatomical scoring method; 4) prospective definitions of interventions and meaningful outcome variables (both morbidity and mortality; 5) relative outcome compared to known standards; and 6) prospective determination of statistical requirements.

Adult trauma scoring models: a critical review

Since the development of the TRISS (Revised Trauma Score and Injury Severity Score) trauma scoring model several alternative models have been developed. Trauma scoring systems can be broadly categorized into anatomically based injury severity models, e.g. NISS (New Injury Severity Score) and ASCOT (A Severity Characterization of Trauma) or data driven models, e.g. ICISS (Insternational Classification of Diseases Injury Severity Score). Trauma scoring models using death/survival as the outcome measure can either be developed using logistic regression or a neural network approach. Assessment of the worth of a model is most commonly performed using receiver operating curve analysis or the Hosmer-Lemeshow statistic. Both of these statistical methods have their inherent weaknesses when applied to trauma scoring model development. This article aims to review four trauma scoring models and to discuss the limitations of the statistical methods used to assess the worth of these models.

Demographic Patterns and Outcomes of Patients in Level I Trauma Centers in Three International Trauma Systems

Introduction

Trauma systems were developed to improve the care for the injured. The designation and elements comprising these systems vary across countries. In this study, we have compared the demographic patterns and patient outcomes of Level I trauma centers in three international trauma systems.

Methods

International multicenter prospective trauma registry-based study, performed in the University Medical Center Utrecht (UMCU), Utrecht, the Netherlands, John Hunter Hospital (JHH), Newcastle, Australia, and Harborview Medical Center (HMC), Seattle, the United States. Inclusion: patients ≥18 years, admitted in 2012, registered in the institutional trauma registry.

Results

In UMCU, JHH, and HMC, respectively, 955, 1146, and 4049 patients met the inclusion criteria of which 300, 412, and 1375 patients with Injury Severity Score (ISS) > 15. Mean ISS was higher in JHH (13.5; p < 0.001) and HMC (13.4; p < 0.001) compared to UMCU (11.7). Unadjusted mortality: UMCU = 6.5 %, JHH = 3.6 %, and HMC = 4.8 %. Adjusted odds of death: JHH = 0.498 [95 % confidence interval (CI) 0.303–0.818] and HMC = 0.473 (95 % CI 0.325–0.690) compared to UMCU. HMC compared to JHH was 1.002 (95 % CI 0.664–1.514). Odds of death patients ISS > 15: JHH = 0.507 (95 % CI 0.300–0.857) and HMC = 0.451 (95 % CI 0.297–0.683) compared to UMCU. HMC = 0.931 (95 % CI 0.608–1.425) compared to JHH. TRISS analysis: UMCU: Ws = 0.787, Z = 1.31, M = 0.87; JHH, Ws = 3.583, Z = 6.7, M = 0.89; HMC, Ws = 3.902, Z = 14.6, M = 0.84.

Conclusion

This study demonstrated substantial differences across centers in patient characteristics and mortality, mainly of neurological cause. Future research must investigate whether the outcome differences remain with nonfatal and long-term outcomes. Furthermore, we must focus on the development of a more valid method to compare systems.

Comparison of risk-adjusted survival in two Scandinavian Level-I trauma centres

BACKGROUND

Assessment of trauma-system performance is important for improving the care of injured patients. The aim of the study was to compare risk-adjusted survival in two Scandinavian Level-I trauma centres.

METHODS

This was an observational, retrospective study of prospectively-collected trauma registry data for patients >14 years from Karolinska University Hospital - Solna (KUH), Sweden, and Oslo University Hospital - Ullevål (OUH), Norway, from 2009-2011. Probability of survival (Ps) was calculated according to the Trauma and Injury Severity Score (TRISS) method. Risk-adjusted survival per patient was calculated by assigning every patient a value corresponding to gained or lost fractional life: Each survivor contributed a reward of 1-Ps and each death a penalty of -Ps. The sum of penalties and rewards, corresponding to the difference between expected and actual mortality, was compared between the centres. We present the data as excess survivors per 100 trauma patients.

RESULTS

There were 4485 admissions at KUH and 3591 at OUH. The proportion of severely injured patients was higher at OUH compared with KUH (Injury Severity Score [ISS] >15: 33.9 % vs. 21.1 %, p <0.001). OUH had a larger proportion of patients >65 years (16.0 % vs. 13.4 %, p <0.001) and greater comorbidity (ASA-PS ≥3: 14.6 % vs. 6.9 %, p <0.001) compared with KUH. The frequency of helicopter transport and presence of prehospital physicians was higher at OUH compared with KUH (27.6 % vs. 15.5 % and 30.5 % vs. 3.7 %, both p <0.001). Secondary admissions were 5.2-fold more common at OUH compared with KUH (p <0.001). There were no differences in 30-day mortality for severely injured patients (ISS >15). Risk-adjusted survival rate was higher at OUH than at KUH for primary (0.59 vs. 0.51) but lower for secondary (1.41 vs. 2.85) admissions (both p <0.001).

CONCLUSION

Adjustments for age as a continuous variable and comorbidity should be made when comparing risk-adjusted survival between hospitals, but this is not possible with the TRISS model. A survival prediction model that takes this into account may be a better choice for Scandinavian trauma populations. The current study could not rule out the influence of the system differences between the centres on risk-adjusted survival.

The Applicability of Trauma and Injury Severity Score for a Blunt Trauma Population in Korea and a Proposal of New Models Using Score Predictors

PURPOSE

The purpose of this study was to verify the utility of existing Trauma and Injury Severity Score (TRISS) coefficients and to propose a new prediction model with a new set of TRISS coefficients or predictors.

MATERIALS AND METHODS

Of the blunt adult trauma patients who were admitted to our hospital in 2014, those eligible for Korea Trauma Data Bank entry were selected to collect the TRISS predictors. The study data were input into the TRISS formula to obtain "probability of survival" values, which were examined for consistency with actual patient survival status. For TRISS coefficients, Major Trauma Outcome Study-derived values revised in 1995 and National Trauma Data Bank-derived and National Sample Project-derived coefficients revised in 2009 were used. Additionally, using a logistic regression method, a new set of coefficients was derived from our medical center's database. Areas under the receiver operating characteristic (ROC) curve (AUC) for each prediction ability were obtained, and a pairwise comparison of ROC curves was performed.

RESULTS

In the statistical analysis, the AUCs (0.879-0.899) for predicting outcomes were lower than those of other countries. However, by adjusting the TRISS score using a continuous variable rather than a code for age, we were able to achieve higher AUCs [0.913 (95% confidence interval, 0.899 to 0.926)].

CONCLUSION

These results support further studies that will allow a more accurate prediction of prognosis for trauma patients. Furthermore, Korean TRISS coefficients or a new prediction model suited for Korea needs to be developed using a sufficiently sized sample.

Evaluation of Probability of Survival using APACHE II & TRISS Method in Orthopaedic Polytrauma Patients in a Tertiary Care Centre

AIM

The aim of the study was to assess the ability of Acute Physiology and Chronic Health Evaluation (APACHE) II scoring system and Trauma and Injury Severity Score (TRISS) method to evaluate chances of survival of orthopaedic polytrauma patients.

MATERIALS AND METHODS

It is a retrospective study carried out at a tertiary care teaching hospital situated in a hilly terrain. The medical records of 535 polytrauma patients admitted to ICU from January 2012 to April 2015 were examined of which only 95 were included into the study. The APACHE II scores were calculated from data at the time of admission, on day 1 after admission and on day 5. Data from casualty department was used to calculate TRISS. For each patient APACHE II and TRISS was used to calculate their probability of death. Receiver operating characteristic curve analysis was used to assess the ability of APACHE II and TRISS to predict mortality.

RESULTS

In the receiver operating characteristic curve analysis, the areas under the curve for TRISS, APACHE II on admission and APACHE II on day one of admission scoring system was 0.831, 0.706, 0.885 respectively. Sensitivity and specificity for TRISS was 83.64 and 77.50 respectively while for APACHE II score on day one of admission was 90.91 and 72.50.

CONCLUSION

The results from the present study showed that APACHE II score on day one of admission was relatively a better predictor than TRISS score and a far better predictor than APACHE II on admission in evaluating probability of survival of a patient.

A comparative study of designated trauma team leaders on trauma patient survival and emergency department length-of-stay

Objectives:

There is controversy over who should serve as the Trauma Team Leader (TTL) at trauma-receiving centres. This study compared survival and emergency department (ED) length-of-stay between patients cared for by 3 different groups of TTLs: surgeons, emergency physicians (EPs) on call for trauma cases and EPs on shift in the ED.

Methods:

We performed a retrospective cohort study involving all adult major blunt trauma patients (aged 17 and older) who were admitted to 2 level I trauma centres and who were entered into a provincial Trauma Registry between March 2000 and April 2002. The study was designed to compare the effect of TTL-type on survival and ED length-of-stay, while controlling for sex, age, and trauma severity as defined by the Injury Severity Score (ISS) and the Revised Trauma Score (RTS). Analysis was performed using linear regression modeling (for the ED lenght-of-stay outcome variable), and logistic regression modeling (for the surivial outcome variable).

Results:

There were 1412 patients enrolled in the study. The study population comprised 74% men and 26% women, with a mean age of 44.7 years (43.1, 46.6 and 42.8 years for surgeons, on-call EPs and on-shift EPs, respectively). The overall mean ISS was 23.2 (23.7 for surgeons, 22.9 for on-call EPs and 23.3 for on-shift EPs) and the overall average RTS was 7.6 (7.6 for surgeons, 7.6 for on-call EPs and 7.5 for on-shift EPs). The overall median ED length-of-stay was 5.3 hours (4.5, 5.3 and 5.6 hours for surgeons, on-call EPs and on-shift EPs, respectively; p = 0.07) and the overall survival was 87% (86% surgeon, 88% on-call EP, 87% on-shift EP; p = 0.08). No statistically significant relationship was found between TTL-type and ED length-of-stay (p = 0.42) or survival (p = 0.43) using multivariate modeling.

Conclusion:

Our results suggest that surgeons, on-call EPs, or on-shift EPs can act as the TTL without a negative impact on patient survival or ED length-of-stay.

Evaluation of probability of survival using trauma and injury severity score method in severe neurotrauma patients

Objective

Despite several limitations, the Trauma Injury Severity Score (TRISS) is normally used to evaluate trauma systems. The aim of this study was to evaluate the preventable trauma death rate using the TRISS method in severe trauma patients with traumatic brain injury using our emergency department data.

Methods

The use of the TRISS formula has been suggested to consider definitively preventable death (DP); the deaths occurred with a probability of survival (Ps) higher than 0.50 and possible preventable death (PP); the deaths occurred with a Ps between 0.50 and 0.25. Deaths in patients with a calculated Ps of less than 0.25 is considered as no-preventable death (NP). A retrospective case review of deaths attributed to mechanical trauma occurring between January 1, 2011 and December 31, 2011 was conducted.

Results

A total of 565 consecutive severe trauma patients with ISS>15 or Revised Trauma Score<7 were admitted in our institute. We excluded a total of 24 patients from our analysis : 22 patients younger than 15 years, and 2 patients with burned injury. Of these, 221 patients with head injury were analyzed in the final study. One hundred eighty-two patients were in DP, 13 in PP and 24 in NP. The calculated predicted mortality rates were 11.13%, 59.04%, and 90.09%. The actual mortality rates were 12.64%, 61.547%, and 91.67%, respectively.

Conclusion

Although it needs to make some improvements, the present study showed that TRISS performed well in predicting survival of traumatic brain injured patients. Also, TRISS is relatively exact and acceptable compared with actual data, as a simple and time-saving method.

Trauma survival prediction in Asian population: a modification of TRISS to improve accuracy

The probability of survival (PS) in blunt trauma as calculated by Trauma and Injury Severity Score (TRISS) has been an indispensable tool in trauma audit. The aim of this study is to explore the predictive performance of the latest updated TRISS model by investigating the Age variable recategorisations and application of local Injury Severity Score (ISS) and Revised Trauma Score (RTS) coefficients in a logistic model using a level I trauma centre database involving Asian population.

METHODS

Prospectively and consecutively collected 5684 trauma patients' data over a 10-year period at a regional level I trauma centre were reviewed. Four modified TRISS (mTRISS) models using Age coefficient from reclassifications of the Age variable according to their correlation with survival by logistic regression on the local dataset were acquired. RTS and ISS coefficients were derived from the local dataset and then applied to the mTRISS models. mTRISS models were compared with the existing Major Trauma Outcome Study (MTOS)-derived TRISS (eTRISS) model. Model 1=Age effect taken as linear; Model 2=Age classified into two groups (0-54, 55+); Model 3=Age classified into four groups (0-15, 16-54, 55-79, 80+) and Model 4=Age classified into two groups (0-69, 70+). Performance measures including sensitivity, specificity, accuracy and area under the Receiver Operating Characteristic (ROC) curve were used to assess the various models. The cross-validation procedure consisted of comparing the P(S) obtained from mTRISS Models 1 and 2 with the P(S) obtained from the MTOS derived from eTRISS.

RESULTS

A 5147 blunt trauma patients' dataset was reviewed. Model 1, where Age was taken as a scale variable, demonstrated a substantial improvement in the survival prediction with 91.6% accuracy in blunt injuries as compared with 89.2% in the MTOS-derived TRISS. The 95% CI for ROC derived from mTRISS Model 1 was (0.923, 0.940), when compared with the hypothesised ROC value 0.886 obtained from eTRISS, it clearly indicated a significant improvement in predicting survival at 5% level. Furthermore, ROCs have shown clearly the superiority of Model 1 over Model 2, and of Model 2 over MTOS-derived TRISS. The recategorisation of the Age variable (Models 3 and 4) also demonstrated improved performance, but their strength was not as intense as in Model 1. Overall, the results point to the adoption of Model 1 as the best model for PS. Cross-validation analysis has further assured the validity of these findings.

CONCLUSIONS

The present study has demonstrated that (1) having the Age variable being dichotomised (cut-off at 55 years) as in the eTRISS, but with the application of a local dataset-derived coefficients give better TRISS survival prediction in Asian blunt trauma patients; (2) improved performance are found with certain recategorisation of the Age variable and (3) the accuracy can further be enhanced if the Age effect is taken to be linear, with the application of local dataset-derived coefficients.

Comparison of the Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation II scoring system, and Trauma and Injury Severity Score method for predicting the outcomes of intensive care unit trauma patients

PURPOSE

The aim of this study was to assess the ability of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) II scoring system, and Trauma and Injury Severity Score (TRISS) method to predict group mortality for intensive care unit (ICU) trauma patients.

METHODS

The medical records of 706 consecutive major trauma patients admitted to the ICU of Samsung Changwon Hospital from May 2006 to April 2010 were retrospectively examined. The SOFA and the APACHE II scores were calculated based on data from the first 24 hours of ICU admission, and the TRISS was calculated using initial laboratory data from the emergency department and operative data. The probability of death was calculated for each patient based on the SOFA score, APACHE II score, and TRISS equations. The ability to predict group mortality for the SOFA score, APACHE II score, and TRISS method was assessed by using 2-by-2 decision matrices and receiver operating characteristic curve analysis and calibration analysis.

RESULTS

In 2-by-2 decision matrices with a decision criterion of 0.5, the sensitivities, specificities, and accuracies were 74.1%, 97.1%, and 92.4%, respectively, for the SOFA score; 58.5%, 99.6%, and 91.1%, respectively, for the APACHE II scoring system; and 52.4%, 94.8%, and 86.0%, respectively, for the TRISS method. In the receiver operating characteristic curve analysis, the areas under the curve for the SOFA score, APACHE II scoring system, and TRISS method were 0.953, 0.950, and 0.922, respectively.

CONCLUSION

The results from the present study showed that the SOFA score was not different from APACHE II scoring system and TRISS in predicting the outcomes for ICU trauma patients. However, the method for calculating SOFA scores is easier and simpler than APACHE II and TRISS.

Improved prediction from revised injury severity classification (RISC) over trauma and injury severity score (TRISS) in an independent evaluation of major trauma patients

The usefulness of the Revised Injury Severity Classification (RISC) analysis was compared with that of the Trauma and Injury Severity Score (TRISS) for evaluating the quality of treatment of severely injured patients at the General Hospital Celje, Slovenia. Over a period of 2 years, data from a cohort of 155 patients treated at the General Hospital Celje were included in the Traumaregister Deutsche Gesellschaft für Unfallchirurgie. The structure of the patient group was compared with that in the registry, and TRISS and RISC analyses were performed. The M statistic (0.83) showed a good match of the distribution of probability of survival between groups. Evaluation of RISC (area under the curve [AUC] 0.94, Hosmer-Lemeshow test 3.5) demonstrated the efficacy of this method in the patient group. TRISS (AUC 0.89, Hosmer-Lemeshow test 21.1) was not a reliable instrument for analysis of treatment of major trauma patients. We believe that RISC should replace TRISS for evaluation of the treatment of major trauma patients.

The regionalization of pediatric health care

Regionalization of health care is a method of providing high-quality, cost-efficient health care to the largest number of patients. Within pediatric medicine, regionalization has been undertaken in 2 areas: neonatal intensive care and pediatric trauma care. The supporting literature for the regionalization of these areas demonstrates the range of studies within this field: studies of neonatal intensive care primarily compare different levels of hospitals, whereas studies of pediatric trauma care primarily compare the impact of institutionalizing a trauma system in a single geographic region. However, neither specialty has been completely regionalized, possibly because of methodologic deficiencies in the evidence base. Research with improved study designs, controlling for differences in illness severity between different hospitals; a systems approach to regionalization studies; and measurement of parental preferences will improve the understanding of the advantages and disadvantages of regionalizing pediatric medicine and will ultimately optimize the outcomes of children.

M-study from an urban trauma center in Tokyo

BACKGROUND

The original Trauma and Injury Severity Score (TRISS) methodology from the Major Trauma Outcome Study (MTOS) is the most widely used outcome prediction model. The coefficients from the MTOS cohorts are still used in the Japan Trauma Data Bank for evaluating the quality of patient care. The purposes are to determine whether the database of this institution is well matched to the MTOS study and whether the original TRISS coefficients are accurate predictors of the patient outcome in Japan.

METHODS

The M-statistic score was calculated based on the trauma registry data from 2000 to 2003 in Teikyo University.

RESULTS

Eight hundred fifty-four cases were analyzed. The crude mortality rate was 10.5%. The mean Injury Severity Score was 15.8 ± 13.6. The mean Revised Trauma Score was 7.00 ± 1.4. The M-statistic score was 0.811.

CONCLUSION

The trauma populations in this study differed significantly from the MTOS. The Modified TRISS coefficients should be adapted for outcome assessment based on the location of the injured population. This is the first report of an M-study from Japan to be published in the English literature.

Evaluation of Quality of Trauma Care in a Local Hospital Using a Customization of ASCOT

OBJECTIVE

Evaluating processes of care and outcomes of injured patients are important if improvements in the quality of care delivered to injured patients are to be accomplished. We applied a customized ASCOT model developed from our database as a tool to criticize the quality of care in a local hospital.

PATIENTS AND METHODS

A total number of 4,096 trauma patients were used to develop new coefficients for customization of ASCOT. These patients were divided randomly into two equal groups. New coefficients for ASCOT were derived from the first set of patients. The newly developed model was validated in the second group of patients and the measures of discrimination (area under the ROC curve) and calibration (Hosmer-Lemeshow goodness of fit) were calculated. Then we used the customized model to calculate the W score in different subgroups of patients treated in a local hospital to evaluate the care offered to patients in each group.

RESULTS

The customized ASCOT had a good discrimination (area under ROC curve = 0.9575) and calibration (Hosmer-Lemeshow goodness of fit p value = 0.7628) in the validation dataset. Using the customized model, we calculated W score in different subgroup of patients treated in a local hospital for a period of six months. The quality of care was worst for laparotomy (W = -13.31) and pelvic fracture (W = -5.56) and best for orthopedic (W = 1.76) operations.

CONCLUSION

We believe that a customization of ASCOT model when used for evaluation of quality of care in a local hospital can be useful for detection of defects and improvement of the process of care delivered to the patients.

The value of trauma registries

Trauma registries are databases that document acute care delivered to patients hospitalised with injuries. They are designed to provide information that can be used to improve the efficiency and quality of trauma care. Indeed, the combination of trauma registry data at regional or national levels can produce very large databases that allow unprecedented opportunities for the evaluation of patient outcomes and inter-hospital comparisons. However, the creation and upkeep of trauma registries requires a substantial investment of money, time and effort, data quality is an important challenge and aggregated trauma data sets rarely represent a population-based sample of trauma. In addition, trauma hospitalisations are already routinely documented in administrative hospital discharge databases. The present review aims to provide evidence that trauma registry data can be used to improve the care dispensed to victims of injury in ways that could not be achieved with information from administrative databases alone. In addition, we will define the structure and purpose of contemporary trauma registries, acknowledge their limitations, and discuss possible ways to make them more useful.

Use of scene vital signs improves TRISS predicted survival in intubated trauma patients

INTRODUCTION

The Trauma Related Injury Severity Score (TRISS) has been previously validated to predict outcomes in nonintubated, nonparalyzed trauma patients. The purpose of this study was to assess the impact of scene vital signs on predicting survival in intubated trauma patients.

METHODS

Our Trauma Registry of the American College of Surgeons was reviewed for all trauma patients admitted between 10/01/04 and 09/30/06, arriving by aeromedical transport. TRISS was evaluated for each patient based on their (1) scene vital signs and (2) arrival vital signs. Additionally, the "TRISS-like" score was calculated for each patient. Expected mortality for each score was measured against observed mortality.

RESULTS

Four thousand four hundred ninety-nine Trauma Registry of the American College of Surgeons patients were admitted during the study period; 695 (15%) were transported by air; 163 patients (23%) arrived intubated; 480 arrived nonintubated. Observed survival in the intubated group was 76%. Observed survival in the nonintubated group was 100%. TRISS using scene vital signs more closely predicted mortality among intubated patients than the other scoring systems (69% versus 39% using TRISS-arrival versus 80% using TRISS-like). Scene vital signs with TRISS also resulted in fewer "unexpected" outcomes (survivors and deaths).

CONCLUSIONS

Traditionally, patients arriving at trauma centers intubated are either excluded from the trauma registry or have their physiological score "modified" to account for pharmacologically altered respiratory rate and Glasgow Coma Scale. In intubated patients, TRISS using scene vital signs more reliably predicts survival and does so with far fewer "unexpected" outcomes than with other available scoring systems.

Different definitions of patient outcome: consequences for performance analysis in trauma

BACKGROUND

Death during acute care hospitalisation is commonly used as a principal outcome indicator in injury research. This endpoint excludes post-hospital trauma-related deaths, which are substantial according to recent US studies. Two additional ways of defining outcome in trauma victims are also used; by end of somatic care, and at 30 days after injury. Our primary aim was to analyse how the different definitions of trauma outcome influence performance analyses. Secondly, we wanted to evaluate whether 30 days mortality after injury, which is widely used in other parts of biomedicine and recommended by the United Nations for use in transport statistics, is a suitable endpoint in trauma research.

MATERIALS AND METHODS

We conducted a retrospective analysis of prospectively collected data from the hospital based trauma registry at Ulleval University Hospital (UUH) in Oslo, Norway. Outcome measure was mortality at discharge from UUH, i.e., by "end of acute care", at end of somatic care defined as discharge from final acute care hospital, and at 30 days after injury. Analyses were performed according to conventional TRISS methodology.

RESULTS

3332 of 3446 patients from the years 2000-2004 were included. Of these, 323 (9.7%) died within 30 days of injury or during somatic care more than 30 days after injury. Mortality varied with outcome definition, with 264 deaths (81.7% of total deaths) before discharge from UUH, 318 (98.4%) before end of somatic care, and 308 (95.4%) within 30 days after injury. TRISS-based trauma system performance evaluation for blunt trauma showed significantly better outcome than predicted with discharge from UUH as outcome definition, whereas for category 30 days after injury, performance was clearly less favourable. Performance for penetrating trauma was not affected, since all deaths occurred before 30 days, and nearly all before discharge from UUH.

CONCLUSIONS

A substantial number of in-hospital deaths following blunt trauma occurs after discharge from the primary institution, i.e., unnoticed when "end of acute care" is used as outcome definition. Consequently, outcome definition influenced performance when comparing our institution to an acknowledged standard. We recommend mortality occurring within 30 days of injury as endpoint in trauma research.

Using information on preexisting conditions to predict mortality from traumatic injury

STUDY OBJECTIVE

Preexisting conditions have been found to be an independent predictor of mortality after trauma. However, no consensus has been reached as to what indicator of preexisting condition status should be used, and the contribution of preexisting conditions to mortality prediction models is unclear. This study aims to identify the most accurate way to model preexisting condition status to predict inhospital trauma mortality and to evaluate the potential gain of adding preexisting condition status to a standard trauma mortality prediction model.

METHODS

The study comprised all patients from the trauma registries of 4 Level I trauma centers. Information provided by individual preexisting conditions was compared to 3 commonly used summary measures: (1) absence/presence of any preexisting condition, (2) number of preexisting conditions, and (3) Charlson Comorbidity Index. The impact of adding preexisting condition status to 2 baseline risk models, the current standard Trauma and Injury Severity Score model and an improved model based on nonparametric transformations of quantitative variables, was evaluated by the area under the receiver operating characteristics curve.

RESULTS

Discrimination for predicting mortality in the improved model was as follows: baseline risk model: area under the receiver operating characteristics curve=0.935; baseline risk model+individually modeled preexisting conditions: area under the receiver operating characteristics curve=0.941; baseline risk model+presence of any preexisting condition: area under the receiver operating characteristics curve=0.937; baseline risk model+number of preexisting conditions: area under the receiver operating characteristics curve=0.939; baseline risk model+Charlson Comorbidity Index: area under the receiver operating characteristics curve=0.938.

CONCLUSION

Preexisting condition status is an independent predictor of mortality from trauma that provides a modest improvement in mortality prediction. The total number of preexisting conditions is a good summary measure of preexisting condition status. The Charlson Comorbidity Index is no better than the total number of preexisting conditions and is therefore not recommended for use in trauma mortality modeling.

Are Patients With Self-Inflicted Injuries More Likely to Die?

BACKGROUND

Suicide represents one of the leading causes of trauma in industrialized countries. However, when compared with unintentional injury and assault, the outcome of self-inflicted injury has not been well described.

METHODS

All patients admitted to a French academic trauma center from January 2002 to December 2004 and listed in a trauma data bank were included in a prospective analysis. Variables including mortality, circumstances (unintentional vs. assault vs. self-inflicted), and mechanism of injury were recorded.

RESULTS

About 1,004 continuous trauma patients were analyzed: 151 (15%) with self-inflicted injuries, 761 (76%) with unintentional injuries, and 91 (9%) with injuries from assault. When compared with patients suffering from unintentional injuries and assault, self-inflicted injury patients presented more frequently after a fall from height (94 of 151 vs. 133 of 759 and 0 of 91, p < 0.05) and with a severe head injury (47 of 151 vs. 172 of 752 and 10 of 91, p < 0.05). They also had a more severe injury (Injury Severity Score, 28 +/- 21 vs. 22 +/- 16 and 12 +/- 10; p < 0.05), a lower probability of survival (Trauma Related Injury Severity Score, 0.71 +/- 0.37 vs. 0.83 +/- 0.28 and 0.92 +/- 0.19; p < 0.05), and survival rate (70% vs. 85% and 93%, p < 0.05). In multivariate analysis, Trauma Related Injury Severity Score (odds ratio, 0.54; 95% confidence interval, 0.45-0.59; p < 0.001), age (odds ratio, 1.17; confidence interval, 1.02-1.34; p < 0.05), and mechanism of trauma (p = 0.01) were independently correlated with the final mortality rate.

CONCLUSIONS

Self-inflicted injury patients presented with a higher mortality rate that was related to increased injury severity. The circumstances surrounding the trauma were not independently associated with an increased odds ratio of death after major trauma.

The casualty profile from the Reading train crash, November 2004: proposals for improved major incident reporting and the application of trauma scoring systems

OBJECTIVE

To report the casualty profile of the major incident at the Royal Berkshire Hospital, Reading, following the Ufton Nervet Train crash, November 2004. To make further proposals regarding major incident reporting and implementation of trauma-scoring systems.

METHOD

Retrospective analysis of emergency department and hospital notes. Calculation of index Injury Severity Score (ISS) and Trauma and Injury Severity Score (TRISS) in all patients.

RESULTS

Of 61 casualties, the majority (74%) were seen in the minors area of our emergency department with a mixture of blunt impact and penetrating glass injuries. One died and 16 were admitted. 10% had an ISS >16. All surviving patients had a TRISS predicted probability of survival >90%.

CONCLUSION

We propose mandatory major incident reporting within 6 months of a major incident to aid development of a national database. As previously proposed, this will aid education and facilitate future major incident planning. We further propose the widespread use of trauma scoring systems to facilitate comparative analysis between major incidents, perhaps extrapolating this to develop a major incident score.

The importance of quality of survival as an outcome measure for an integrated trauma system

Risk-adjusted survival rates have been the principle mode of comparison between trauma systems. In mature trauma systems, it is possible that there will be further improvements in survival but these are likely to be small. In the future, the largest gains will come from quality of life and improved function of the survivors. The issues related to measuring quality of survival for trauma systems are reviewed, including feasibility, ethical considerations, risk adjustment of outcomes of survivors, and challenges for selection of instruments and administration. In addition, the preliminary experiences of measuring outcomes in survivors through the Victorian State Trauma Registry are discussed. Although function and quality of life have been identified as important factors to measure in trauma populations, a standardised protocol has not been established. The experience in Victoria suggests that monitoring of population-based outcomes in survivors is feasible and may create the basis for benchmarking the level of morbidity in survivors.

Factors influencing pediatric Injury Severity Score and Glasgow Coma Scale in pediatric automobile crashes: results from the Crash Injury Research Engineering Network

BACKGROUND/PURPOSE

Motor vehicle crashes account for more than 50% of pediatric injuries. Triage of pediatric patients to appropriate centers can be based on the crash/injury characteristics. Pediatric motor vehicle crash/injury characteristics can be determined from an in vitro laboratory using child crash dummies. However, to date, no detailed data with respect to outcomes and crash mechanism have been presented with a pediatric in vivo model.

METHODS

The Crash Injury Research Engineering Network is comprised of 10 level 1 trauma centers. Crashes were examined with regard to age, crash severity (DeltaV), crash direction, restraint use, and airbag deployment. Multiple logistic regression analysis was performed with Injury Severity Score (ISS) and Glasgow Coma Scale (GCS) as outcomes. Standard age groupings (0-4, 5-9, 10-14, and 15-18) were used. The database is biases toward a survivor population with few fatalities.

RESULTS

Four hundred sixty-one motor vehicle crashes with 2500 injuries were analyzed (242 boys, 219 girls). Irrespective of age, DeltaV > 30 mph resulted in increased ISS and decreased GCS (eg, for 0-4 years, DeltaV < 30: ISS = 10, GCS = 13.5 vs DeltaV > 30: ISS = 19.5, GCS = 10.6; P < .007, < .002, respectively). Controlling for DeltaV, children in lateral crashes had increased ISS and decreased GCS versus those in frontal crashes. Airbag deployment was protective for children 15 to 18 years old and resulted in a lower ISS and higher GCS (odds ratio, 2.1; 95% confidence interval, 0.9-4.6). Front-seat passengers suffered more severe (ISS > 15) injuries than did backseat passengers (odds ratio, 1.7; 95% confidence interval, 0.7-3.4). A trend was noted for children younger than 12 years sitting in the front seat to have increased ISS and decreased GCS with airbag deployment but was limited by case number.

CONCLUSION

A reproducible pattern of increased ISS and lower GCS characterized by high severity, lateral crashes in children was noted. Further analysis of the specific injuries as a function and the crash characteristic can help guide management and prevention strategies.

Assessing quality of care in a trauma referral center: benchmarking performance by TRISS-based statistics or by analysis of stratified ISS data?

BACKGROUND

Using prospectively collected data from Ulleval University Hospital in Norway, standard TRISS-based methods with case mix correction were compared with analysis based on ISS stratified data.

METHODS

Reference data were The Major Trauma Outcome Study (MTOS) controlled sites, used for calculation of AIS 90 based TRISS coefficients. Present TRISS convention requires RTS scoring on hospital admission, excluding many severely injured patients intubated before arrival. Therefore, all Ulleval patients were RTS scored using prehospital data if needed.

RESULTS

There was 6.6% of MTOS controlled sites patients (mortality rate 26.7%) that had been excluded before estimation of TRISS coefficients because of lack of data for Ps calculation. Analyses based on ISS stratified data included these patients and indicated significant better performance at Ulleval for blunt, but not for penetrating trauma. No TRISS-based analysis detected this difference.

CONCLUSIONS

The RTS convention should be changed to reduce patient exclusion. Presently, stratified ISS based data should also be analyzed.

The usefulness of trauma scores in determining the life threatening condition of trauma victims for writing medical-legal reports

OBJECTIVES

In the Turkish legal system the severity of the victim's injury determines the severity of the criminal penalty, and the life threatening condition stated in the medical-legal report is one of the main determinants for injury severity. The aim of this study is to investigate the effectiveness and usefulness of the trauma scores in determining the life threatening condition of trauma victims from the forensic aspect in order to write accurate medical-legal reports.

METHODS

Data of 296 forensic cases with blunt and penetrating trauma were obtained. The life threatening condition of patients stated in the medical-legal reports according to the criteria based on traditional forensic opinion were examined. For each case, Injury Severity Score (ISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) were calculated. The ROC curve analysis was used to investigate the success of the trauma scores in distinguishing patients with/without life threatening conditions. Logistic regression analysis was performed to measure the association between trauma scores and life threatening conditions.

RESULTS

The relations between all scores and groups (with and without life threatening risk) were found statistically significant. ISS was the most successful method in distinguishing traumatised patients both in a life threatening or non life threatening condition.

CONCLUSIONS

Trauma scores can be used for making more objective, standardised, and accurate judgement on whether the injury was a life threatening one or not. These advantages of using trauma scores in such situations will also be helpful for the conclusion of the lawsuits shortly, but further studies are needed to confirm these findings.

Patterns of severe injury in pediatric car crash victims: Crash Injury Research Engineering Network database

BACKGROUND/PURPOSE

Motor vehicle crashes (MVCs) account for 50% of pediatric trauma. Safety improvements are typically tested with child crash dummies using an in vitro model. The Crash Injury Research Engineering Network (CIREN) provides an in vivo validation process. Previous research suggest that children in lateral crashes or front-seat locations have higher Injury Severity Scale scores and lower Glasgow Coma Scale scores than those in frontal-impact crashes. However, specific injury patterns and crash characteristics have not been characterized.

METHODS

Data were collected from the CIREN multidisciplinary crash reconstruction network (10 pediatric trauma centers). Injuries were examined with regard to crash direction (frontal/lateral), restraint use, seat location, and change in velocity at impact (DeltaV). Injuries were limited to Abbreviated Injury Scale (AIS) scores of 3 or higher and included head, thoracic, abdominal, pelvic, spine, and long bone (orthopedic) injuries. Standard age groupings (0-4, 5-9, 10-14, and 15-18 years) were used. Statistical analyses used Fisher's Exact test and multiple logistic regressions.

RESULTS

Four hundred seventeen MVCs with 2500 injuries were analyzed (males = 219, females = 198). Controlling for DeltaV and age, children in lateral-impact crashes (n = 232) were significantly more likely to suffer severe injuries to the head and thorax as compared with children in frontal crashes (n = 185), who were more likely to suffer severe spine and orthopedic injuries. Children in a front-seat (n = 236) vs those in a back-seat (n = 169) position had more injuries to the thoracic (27% vs 17%), abdominal (21% vs 13%), pelvic (11% vs 1%), and orthopedic (28% vs 10%) regions (P < .05 for all). Seat belts were protective for pelvic (5% vs 12% unbelted) and orthopedic (15% vs 40%) injuries (odds ratio = 3, P < .01 for both).

CONCLUSION

A reproducible pattern of injury is noted for children involved in lateral-impact crashes characterized by head and chest injuries. The Injury Severity Scale scores were higher for children in front-seat positions. Increased lateral-impact safety measures such as mandatory side curtain airbags may decrease morbidity. Furthermore, continued public education for positioning children in the back seat of cars is warranted.

The Trauma Registry as a Statewide Quality Improvement Tool

BACKGROUND

Trauma registries have been developed to describe the pattern of trauma and trauma workload, provide data for research, and to demonstrate changes in patient outcomes. Quality improvement using trauma registries at a system-wide level has been difficult to achieve. In Victoria, Australia, a statewide trauma system and trauma registry has been established to monitor and feedback the process of management and outcomes of major trauma patients across all healthcare providers.

METHODS

The development and implementation of the Victorian State Trauma Registry (VSTR), including its role as a quality monitoring tool and results from the first 2 years of operation, are provided.

RESULTS

More than 80% of major trauma patients are being managed at major trauma services and standardized death rates are comparable with international standards. Quality indicators identify some areas for improvement.

CONCLUSION

VSTR data indicate that the statewide trauma system is working well and provides a method for ongoing monitoring and trauma care feedback.

Prehospital intubation and chest decompression is associated with unexpected survival in major thoracic blunt trauma

OBJECTIVE

Application of the Trauma and Injury Severity Score (TRISS) to a trauma population identifies patients with 'unexpected survival'. This study used TRISS analysis to identify 'unexpected survivors' suffering major thoracic trauma, who survived to hospital discharge. Further analysis determined prehospital interventions that appeared to contribute to 'unexpected survival'.

METHODS

The present study was a single-centre, retrospective case review with comparative statistical analysis. Patients were identified from the Alfred Trauma Registry between 1 July 2002 and 30 June 2003.

RESULTS

There were 336 adult trauma patients treated at The Alfred Trauma Centre with an Injury Severity Score >15 (major trauma) and at least one thoracic Anatomical Injury Score of 3 (severe) or greater. Of the eligible patients, 322/336 (95.8%, 95%[confidence interval] CI 95.1-96.5%) had complete data available for analysis. The study population mortality was 42/322 (13.0%, 95% CI 12.3-13.7%). There were 20 'unexpected survivors' (5.9%) and 5 (1.5%) 'unexpected deaths' on TRISS analysis. Chest decompression and/or endotracheal intubation prehospital was performed on 16/20 'unexpected survivors'. GCS for 'unexpected survivors' and 'expected deaths' (3.8 vs 3.5, P = 0.27) was not a predictor of survival. Respiratory rate per minute (16.2 vs 8.8, P = 0.01) and systolic blood pressure - mmHg (98 vs 80, P = 0.03) were significantly greater in the 'unexpected survivors' group compared with the 'expected death' group.

CONCLUSION

For patients sustaining severe thoracic blunt trauma, prehospital intubation and chest decompression appear to be associated with unexpected survival. A low GCS at scene is not predictive of 'unexpected survival' or 'expected death'.

The injury scale--a valuable tool for forensic documentation of trauma

An accurate method for quantitatively summarizing injury severity has many potential applications. The ability to predict outcome from trauma (i.e., mortality) is perhaps the most fundamental use of injury severity scoring, a use that arises from the patient's and the family's desires to know the prognosis. Field trauma scoring also is used to facilitate rational pre-hospital triage decisions, thereby minimizing the time from injury occurrence to definitive management. Another use of trauma scoring is for quality assurance by allowing evaluation of trauma care both within and between trauma centers, a contentious and controversial area that is likely to only increase in importance. However, the most important role for injury severity scoring is in trauma care research. Scientific study of the epidemiology of trauma and trauma outcomes would not be possible otherwise. Injury severity scoring is indispensable in stratifying patients into comparable groups for prospective clinical trials. Similarly, this technique can be used retrospectively to identify and control for differences in baseline injury severity between patient populations. More recently, physicians suggested that injury severity scoring could provide objective information for end-of-life decision-making and resource allocation. Unfortunately, trauma mortality prediction in the individual patient is limited and fraught with uncertainty. In fact, decisions for individual patients should never be based solely on a statistically derived injury severity score.

Pediatric trauma patients with isolated airway compromise or Glasgow Coma Scale less than 8: does immediate attending surgeon's presence upon arrival make a difference?

BACKGROUND/PURPOSE

Optimal trauma care requires an attending pediatric surgeon to head a trauma team for the most severely injured patients. Recently, the American College of Surgeons-Committee on Trauma has added "Glasgow Coma Scale (GCS) <8" and "airway compromise" to the existing anatomical and physiological criteria for immediate attending presence. This report analyzes the outcome of children who met these isolated criteria and were treated before the change in guidelines was made.

METHODS

The trauma registry of this level I trauma center was queried for all pediatric patients with GCS <8 or airway compromise. Age, sex, initial GCS, Revised Trauma Score, Injury Severity Score, outcome, and probability of survival (TRISS methodology) were recorded. The subgroup of patients for whom an attending surgeon was not immediately present was further analyzed.

RESULTS

Over a 5-year period, 2895 trauma patients (aged 0-16 years) were admitted. One hundred fifteen patients had a GCS <8 and/or airway compromise. In 61 cases, an attending surgeon was not present upon patient arrival. Of these patients, 24 died (group D), 15 were discharged to a rehabilitation facility (group R), and 22 were discharged home (group H). Ten patients with a probability of survival of lower than 0.5 survived. Only 4 of the 24 patients who died had a probability of survival of >0.5 (mean, 0.697). All 4 had an Injury Severity Score >25 and a GCS < or =4. All deaths were reviewed through a quality improvement program and were deemed nonpreventable by objective reviewers. Patient outcome was not affected by the presence or absence of an attending surgeon upon patient arrival.

CONCLUSIONS

Outcome of severely injured children with GCS <8 or airway compromise met and, in some cases, exceeded expectations of survival according to the TRISS methodology. The lack of immediate attending surgeon's presence does not appear to have negatively influenced the outcome in these children. Based on this series, there is no evidence to justify mandatory immediate presence of an attending surgeon for these 2 criteria alone.

Índices de trauma em pacientes submetidos à laparotomia

OBJETIVO: O trauma é um problema de saúde pública de enormes proporções. Constitui-se na principal causa de óbitos na população jovem. O Major Trauma Outcome Study (MTOS) é um estudo descritivo e retrospectivo da gravidade das lesões e evolução dos pacientes, considerado como o maior arquivo contemporâneo de informações descritivas de traumatizados. O objetivo do presente estudo é comparar o cálculo retrospectivo do New Injury Severity Score (NISS) com o Injury Severity Score (ISS) já calculado prospectivamente, utilizando o Trauma and Injury Severity Score (TRISS) e uma simples modificação deste índice, denominado de NTRISS (New Trauma and Injury Severity Score), e também comparar esta população submetida à laparotomia com os pacientes do MTOS. MÉTODO: Foram estudados 1.380 pacientes adultos traumatizados e submetidos à laparotomia na Disciplina de Cirurgia do Trauma da Unicamp, em Campinas, durante um período de oito anos. Os dados avaliados foram: demográficos, causa do trauma (fechado ou penetrante, ferimento por projétil de arma de fogo ou arma branca), estado fisiológico na admissão (RTS), diagnóstico anatômico de lesões (ATI, ISS e NISS), probabilidade de sobrevida utilizando o TRISS e o NTRISS, e a evolução do paciente (sobrevivência ou óbito). Foram utilizadas as estatísticas Z e W, inicialmente descritas por Flora, a fim de comparar a predição de óbitos ou sobreviventes com o estudo controle (MTOS). RESULTADOS: A maioria dos pacientes (88,3%) era do sexo masculino e jovem (média de idade de 30,4 anos). O ferimento por projétil de arma de fogo foi o mecanismo de trauma mais freqüente, com 641 casos (46,4%). Quatrocentos e trinta pacientes (31,2%) sofreram trauma fechado. As médias do ATI, ISS e NISS foram, respectivamente, de 12,3, 17,6 e 22,1. A taxa global de mortalidade foi de 16,8% e os pacientes com trauma contuso tiveram a maior mortalidade (29,3%). O NISS identificou melhor os sobreviventes e óbitos se comparado ao ISS, obtendo-se uma maior especificidade com o NTRISS. Foi observado um número significativamente menor de sobreviventes do que o esperado pelo estudo basal, com Z -16,24 com o TRISS e Z -9,40 se aplicado o NTRISS. Variações no valor da estatística W para cada paciente mostraram uma diferença no número de óbitos equivalente a 7,89 mais casos de óbito do que o esperado pelo MTOS, por 100 pacientes tratados, ao se empregar o TRISS, enquanto que estes valores foram reduzidos para 5,14 utilizando-se o NTRISS. CONCLUSÕES: Os métodos utilizados para cálculo da probabilidade de sobrevivência apresentaram limitações, particularmente nesta população com predomínio dos traumas penetrantes. O NISS, com o seu derivado NTRISS, foi o escore que obteve uma melhor predição de sobrevivência se comparado com o ISS. Os resultados obtidos com o TRISS e NTRISS foram estatisticamente piores do que os do MTOS, porém este processo de monitorização destes pacientes traumatizados tem sido importante para assegurar uma condição continuada de controle de qualidade.

Predicting outcome after multiple trauma: which scoring system?

We have undertaken a review of the commonly used scoring systems to identify advantages and possible pitfalls involved in their use. Currently, there is a variety of systems available for scoring trauma severity. Some of them are based on the anatomical description of the injuries, whilst others are based on physiological parameters. The most widely used systems for the purpose of predicting outcome after trauma are based on combined anatomical and physiological parameters. Systems such as the Injury Severity Score (ISS) and the Trauma Injury Severity Score (TRISS) have served some useful purposes and have proved popular over time, but it now seems that there is no ideal scoring system available. The task of incorporating various factors such as pre-existing morbidity, age, immunological differences and different genetic predispositions has made the prospect of creating a universally acceptable and applicable trauma-scoring system extremely arduous, if not impossible. Therefore caution should be exercised when using any of the existing scoring systems until an ideal one becomes available.

Improving the TRISS Methodology by Restructuring Age Categories and Adding Comorbidities

BACKGROUND

The Trauma and Injury Severity Score (TRISS) methodology was developed to predict the probability of survival after trauma. Despite many criticisms, this methodology remains in common use. The purpose of this study was to show that improving the stratification for age and adding an adjustment for comorbidity significantly increases the predictive accuracy of the TRISS model.

METHODS

The trauma registry and the hospital administrative database of a regional trauma center were used to identify all blunt trauma patients older than 14 years of age admitted with International Classification of Diseases, Ninth Revision codes 800 to 959 from April 1993 to March 2001. Each individual medical record was then reviewed to ascertain the Revised Trauma Score, the Injury Severity Score, the age of the patients, and the presence of eight comorbidities. The outcome variable was the status at discharge: alive or dead. The study population was divided into two subsamples of equal size using a random sampling method. Logistic regression was used to develop models on the first subsample; a second subsample was used for cross-validation of the models. The original TRISS and three TRISS-derived models were created using different categorizations of Revised Trauma Score, Injury Severity Score, and age. A new model labeled TRISSCOM was created that included an additional term for the presence of comorbidity.

RESULTS

There were 5,672 blunt trauma patients, 2,836 in each group. For original TRISS, the Hosmer-Lemeshow statistic (HL) was 179.1 and the area under the receiver operating characteristic (AUROC) curve was 0.873. Sensitivity and specificity were 99.0% and 27.8%, respectively. For the best modified TRISS model, the HL statistic was 20.35, the AUROC curve was 0.902, the sensitivity was 99.0%, and the specificity was 27.8%. For TRISSCOM, the HL statistic was 14.95 and the AUROC curve was 0.918. Sensitivity and specificity were 99.0% and 29.7%, respectively. The difference between the two models almost reached statistical significance (p = 0.086). When TRISSCOM was applied to the cross-validation group, the HL statistic was 10.48 and the AUROC curve was 0.914. The sensitivity was 98.6% and the specificity was 34.9%.

CONCLUSION

TRISSCOM can predict survival more accurately than models that do not include comorbidity. A better categorization of age and the inclusion of comorbid conditions in the logistic model significantly improves the predictive performance of TRISS.

Does volume matter? The effect of trauma surgeons' caseload on mortality

BACKGROUND

Evidence suggests that trauma centers treating high volumes of severely injured patients produce lower mortality rates than those with low volumes. However, the effect of individual surgeons' trauma caseload on outcomes has not been studied. This study compares outcomes between high-volume (HV) trauma surgeons admitting many patients with high injury severity, and low-volume (LV) surgeons treating fewer critical patients per year.

METHODS

All trauma patients admitted to a large Level I trauma center over a 12-year period were assigned to either the HV or LV group, depending on the yearly volume of their admitting surgeon. Surgeons treating > 35 severely injured (Injury Severity Score > 15) patients per year were considered HV. Student's t test and chi2 analysis were used to test comparability of LV and HV patient groups and to compare mortality rates. Mortality rates of HV and LV surgeons' patients were compared in six injury patterns selected to represent moderate to severe injury. TRISS methodology (z score) was also used to assess outcomes in the two groups. The inherent bias of the TRISS method in comparing trauma outcomes was minimized by the homogeneity of the studied patient population.

RESULTS

A total of 16,481 patients were admitted to HV surgeons, and 4,214 patients were admitted to LV surgeons. In all subgroups, HV and LV patients were similar regarding age, sex, physiologic status at admission, injury pattern, and injury severity. Mortality rates for HV and LV surgeons were not significantly different between the two groups in any injury pattern. The z score was 1.88 in the HV patient group versus 0.47 in the LV group.

CONCLUSION

Within a single institution, mortality rates for patients treated by surgeons admitting many severely injured patients were not significantly different from low-volume surgeons' patients, although there was a trend toward higher mortality in the less active surgeons' patients in some subgroups.