The New Injury Severity Score and the evaluation of pediatric trauma

Comparison of nine trauma scoring systems in prediction of inhospital outcomes of pediatric trauma patients: a multicenter study

Hereby, we aimed to comprehensively compare different scoring systems for pediatric trauma and their ability to predict in-hospital mortality and intensive care unit (ICU) admission. The current registry-based multicenter study encompassed a comprehensive dataset of 6709 pediatric trauma patients aged ≤ 18 years from July 2016 to September 2023. To ascertain the predictive efficacy of the scoring systems, the area under the receiver operating characteristic curve (AUC) was calculated. A total of 720 individuals (10.7%) required admission to the ICU. The mortality rate was 1.1% (n = 72). The most predictive scoring system for in-hospital mortality was the adjusted trauma and injury severity score (aTRISS) (AUC = 0.982), followed by trauma and injury severity score (TRISS) (AUC = 0.980), new trauma and injury severity score (NTRISS) (AUC = 0.972), Glasgow coma scale (GCS) (AUC = 0.9546), revised trauma score (RTS) (AUC = 0.944), pre-hospital index (PHI) (AUC = 0.936), injury severity score (ISS) (AUC = 0.901), new injury severity score (NISS) (AUC = 0.900), and abbreviated injury scale (AIS) (AUC = 0.734). Given the predictive performance of the scoring systems for ICU admission, NTRISS had the highest predictive performance (AUC = 0.837), followed by aTRISS (AUC = 0.836), TRISS (AUC = 0.823), ISS (AUC = 0.807), NISS (AUC = 0.805), GCS (AUC = 0.735), RTS (AUC = 0.698), PHI (AUC = 0.662), and AIS (AUC = 0.651). In the present study, we concluded the superiority of the TRISS and its two derived counterparts, aTRISS and NTRISS, compared to other scoring systems, to efficiently discerning individuals who possess a heightened susceptibility to unfavorable consequences. The significance of these findings underscores the necessity of incorporating these metrics into the realm of clinical practice.

External validation of the PRESTO pediatric tool for predicting in-hospital mortality from traumatic injury

BACKGROUND

Benchmarking is crucial for quality improvement of trauma systems. The Pediatric Resuscitation and Trauma Outcome (PRESTO) model allows risk-adjusted comparisons of in-hospital mortality for pediatric trauma populations in under-resourced environments. Our aim was to validate PRESTO in a high-resource setting using provincial Trauma Registry (TR) data and compare it to the standard benchmarking model, the Injury Severity Score (ISS).

METHODS

This retrospective case-control study collected demographic, vital sign, and outcome data from the TR for patients aged <16 years sustaining major trauma from 2013 to 2021. The PRESTO model estimates predicted probability of in-hospital mortality (Pm) using the age, heart rate, blood pressure, oxygen saturation, neurological status, and use of airway supplementation. PRESTO was assessed by comparison of Pm in patients who died and survived and comparison of area under the receiver-operator curve (AUROC) with that of ISS. Statistical analysis was performed using R.

RESULTS

We included 647 patients, of which 69 died in-hospital (11%). The cohort was 37% female, with a median age of 8 and median ISS of 17. The median Pm for cases was significantly higher compared to controls (1.0 vs. 5.2 × 10^-5, p < 0.001). The AUROC for PRESTO and ISS were not significantly different (0.819 and 0.816, respectively; p = 0.95).

CONCLUSION

PRESTO is valid in a resource-rich environment, such as a Canadian province. It performs equally well to ISS but is simpler to derive. In the future, PRESTO may serve to benchmark levels of in-hospital mortality within or across institutions over time across Canada.

Predictors of 12 month functional outcomes and length of stay of severely injured children in NSW, Australia. A longitudinal multi-centre study

BACKGROUND

The majority of paediatric injury outcomes studies focus on mortality rather than the impact on long-term quality of life, health care use and other health-related outcomes. This study sought to determine predictors of 12-month functional and psychosocial outcomes for children sustaining major injury in NSW.

METHODS

The study included all children < 16 years requiring intensive care or an injury severity score (ISS) ≥ 9 treated in NSW at a paediatric trauma centre (PTC). Children were identified through the three PTCs and NSW Trauma Registry. The paediatric Quality of Life Inventory (PedsQL) and EuroQol five-dimensional EQ-5D-Y were used to measure HRQoL post-injury, completed via parent/carer proxy recruited through NSW PTCs.

RESULTS

There were 510 children treated at the three NSW PTCs during the 15-month study period. The mean (SD) age was 6.7 (6.0) years, with a median NISS (New Injury Severity Score) of 11 (IQR: 9-18). Regression analysis showed worse psychosocial health at twelve months was associated with hospital length of stay (LoS) and number of body regions injured (F₂,₆₅ = 5.85, p = 0.005). Physical outcome was associated with LoS and intensive care unit (ICU) admission (F_2,66 = 13.48, p < 0.001). Hospital LoS was significantly associated with NISS and head injury (F_2,398 = 51.5, p < 0.001).

CONCLUSION

Hospital length of stay and polytrauma are independent factors that negatively influence psychological and physical outcomes of children with major injuries. Early intervention to enable emotional well-being, discharge home and long-term follow up such as dedicated family support and rehabilitation at home could reduce preventable poor outcomes.

New injury severity score (NISS) outperforms injury severity score (ISS) in the evaluation of severe blunt trauma patients

PURPOSE

The injury severity score (ISS) and new injury severity score (NISS) have been widely used in trauma evaluation. However, which scoring system is better in trauma outcome prediction is still disputed. The purpose of this study is to evaluate the value of the two scoring systems in predicting trauma outcomes, including mortality, intensive care unit (ICU) admission and ICU length of stay.

METHODS

The data were collected retrospectively from three hospitals in Zhejiang province, China. The comparisons of NISS and ISS in predicting outcomes were performed by using receiver operator characteristic (ROC) curves and Hosmer-Lemeshow statistics.

RESULTS

A total of 1825 blunt trauma patients were enrolled in our study. Finally, 1243 patients were admitted to ICU, and 215 patients died before discharge. The ISS and NISS were equivalent in predicting mortality (area under ORC curve [AUC]: 0.886 vs. 0.887, p = 0.9113). But for the patients with ISS ≥25, NISS showed better performance in predicting mortality. NISS was also significantly better than ISS in predicting ICU admission and prolonged ICU length of stay.

CONCLUSION

NISS outperforms ISS in predicting the outcomes for severe blunt trauma and can be an essential supplement of ISS. Considering the convenience of NISS in calculation, it is advantageous to promote NISS in China's primary hospitals.

Prediction of mortality in severely injured patients with facial bone fractures

PURPOSE

Identify the most common concomitant injuries associated with facial trauma, and compare the efficacy of various scoring systems in estimation of mortality risks in this category of patients.

METHODS

The study evaluated patients with facial and concomitant injuries, who received the multidisciplinary treatment in a specialized trauma hospital. Values of New Injury Severity Score, Glasgow Coma Scale, Facial Injury Severity Scale, age, and length of hospital stay were statistically analysed to determine presence of relationships between these indicators and define factors that significantly associated with lethal outcome.

RESULTS

During 6-year observation period, 719 patients were treated with multiple or combined maxillofacial trauma, brain injuries and polytrauma. Mainly with isolated midface bones (49.7%), pan-facial (34.6%), mandible (12.9%), and frontal bone and walls (2.8%) fractures. Mortality was (2.2%). The mortality rates in patients with severe pan-facial fractures were higher (p = 0.008) than in single anatomical area (6% vs 1.5%). Age, GCS, and NISS were the most reliable indicator of lethal outcome.

CONCLUSION

Age, Glasgow Coma Scale and New Injury Severity Score main factors, that predicts lethal outcome with high accuracy. New Injury Severity Score value ≥ 41 is a critical level for survival prognosis and should be considered in treatment planning and management of this category of patients.

Retrospective evaluation of the BIG score to predict mortality in pediatric blunt trauma

OBJECTIVES

This study's objective was to measure the criterion validity of the BIG score (a new pediatric trauma score composed of the initial base deficit [BD], international normalized ratio [INR], and Glasgow Coma Scale [GCS]) to predict in-hospital mortality among children admitted to the emergency department with blunt trauma requiring an admission to the intensive care unit, knowing that a score <16 identifies children with a high probability of survival.

METHODS

This was a retrospective cohort study performed in a single tertiary care pediatric hospital between 2008 and 2016. Participants were all children admitted to the emergency department for a blunt trauma requiring intensive care unit admission or who died in the emergency department. The primary analysis was the association between a BIG score ≥16 and in-hospital mortality.

RESULTS

Twenty-eight children died among the 336 who met the inclusion criteria. Two hundred eighty-four children had information on the three components of the BIG score, and they were included in the primary analysis. A BIG score ≥16 demonstrated a sensitivity of 0.93 (95% confidence interval [CI]: 0.76-0.98) and specificity of 0.83 (95% CI: 0.78-0.87) to identify mortality. Using receiver operating characteristic curves, the area under the curve was higher for the BIG score (0.97; 95% IC: 0.95-0.99) in comparison to the Injury Severity Score (0.78; 95% IC: 0.71-0.85).

CONCLUSION

In this retrospective cohort, the BIG score was an excellent predictor of survival for children admitted to the emergency department following a blunt trauma.

Comparison of ISS, NISS, and RTS score as predictor of mortality in pediatric fall

Background

Studies to identify an ideal trauma score tool representing prediction of outcomes of the pediatric fall patient remains elusive. Our study was undertaken to identify better predictor of mortality in the pediatric fall patients.

Methods

Data was retrieved from prospectively maintained trauma registry project at level 1 trauma center developed as part of Multicentric Project—Towards Improving Trauma Care Outcomes (TITCO) in India. Single center data retrieved from a prospectively maintained trauma registry at a level 1 trauma center, New Delhi, for a period ranging from 1 October 2013 to 17 February 2015 was evaluated. Standard anatomic scores Injury Severity Score (ISS) and New Injury Severity Score (NISS) were compared with physiologic score Revised Trauma Score (RTS) using receiver operating curve (ROC).

Results

Heart rate and RTS had a statistical difference among the survivors to nonsurvivors. ISS, NISS, and RTS were having 50, 50, and 86% of area under the curve on ROCs, and RTS was statistically significant among them.

Conclusions

Physiologically based trauma score systems (RTS) are much better predictors of inhospital mortality in comparison to anatomical based scoring systems (ISS and NISS) for unintentional pediatric falls.

The value of the injury severity score in pediatric trauma: Time for a new definition of severe injury?

BACKGROUND

The Injury Severity Score (ISS) is the most commonly used injury scoring system in trauma research and benchmarking. An ISS greater than 15 conventionally defines severe injury; however, no studies evaluate whether ISS performs similarly between adults and children. Our objective was to evaluate ISS and Abbreviated Injury Scale (AIS) to predict mortality and define optimal thresholds of severe injury in pediatric trauma.

METHODS

Patients from the Pennsylvania trauma registry 2000-2013 were included. Children were defined as younger than 16 years. Logistic regression predicted mortality from ISS for children and adults. The optimal ISS cutoff for mortality that maximized diagnostic characteristics was determined in children. Regression also evaluated the association between mortality and maximum AIS in each body region, controlling for age, mechanism, and nonaccidental trauma. Analysis was performed in single and multisystem injuries. Sensitivity analyses with alternative outcomes were performed.

RESULTS

Included were 352,127 adults and 50,579 children. Children had similar predicted mortality at ISS of 25 as adults at ISS of 15 (5%). The optimal ISS cutoff in children was ISS greater than 25 and had a positive predictive value of 19% and negative predictive value of 99% compared to a positive predictive value of 7% and negative predictive value of 99% for ISS greater than 15 to predict mortality. In single-system-injured children, mortality was associated with head (odds ratio, 4.80; 95% confidence interval, 2.61-8.84; p < 0.01) and chest AIS (odds ratio, 3.55; 95% confidence interval, 1.81-6.97; p < 0.01), but not abdomen, face, neck, spine, or extremity AIS (p > 0.05). For multisystem injury, all body region AIS scores were associated with mortality except extremities. Sensitivity analysis demonstrated ISS greater than 23 to predict need for full trauma activation, and ISS greater than 26 to predict impaired functional independence were optimal thresholds.

CONCLUSION

An ISS greater than 25 may be a more appropriate definition of severe injury in children. Pattern of injury is important, as only head and chest injury drive mortality in single-system-injured children. These findings should be considered in benchmarking and performance improvement efforts.

LEVEL OF EVIDENCE

Epidemiologic study, level III.

Expert Perspectives on Time Sensitivity and a Related Metric for Children Involved in Motor Vehicle Crashes

OBJECTIVE

Advanced Automatic Crash Notification (AACN) uses vehicle telemetry data to predict risk of serious injury among motor vehicle crash occupants and can thus improve the accuracy with which injured children are triaged by first responders. To better define serious injury for AACN systems (which typically use Abbreviated Injury Scale [AIS] metrics), an age-specific approach evaluating severity, time sensitivity (TS), and predictability of injury has been developed. This study outlines the development of the TS score.

METHODS

The 95% most frequent AIS 2+ injuries in a national motor vehicle crash data set spanning 2000 to 2011 were determined for the following age groups: 0 to 4, 5 to 9, 10 to 14, and 15 to 18 years. For each age-specific injury, clinicians with pediatric trauma expertise were asked if treatment at a trauma center was required and were asked about the urgency of treatment. A TS score (range 0-1) was calculated by combining the mean trauma center decision and urgency scores.

RESULTS

A total of 30 to 32 responses were obtained for each age-specific injury. The most frequent motor vehicle crash-induced injuries in the younger groups received significantly higher scores than those in the older groups (median TS score 0 to 4 years: 0.89, 5-9 years: 0.87, 10-14 years: 0.82, 15-18 years: 0.72, P < .001). Large variations in TS existed within each AIS severity level; for example, scores among AIS 2 injuries in 0- to 4-year-olds ranged from 0.12 to 0.98.

CONCLUSIONS

The TS of common pediatric injuries varies on the basis of age and may not be accurately reflected by AIS metrics. AIS may not capture all aspects of injury that should be considered by AACN systems.

Systematic review and need assessment of pediatric trauma outcome benchmarking tools for low-resource settings

INTRODUCTION

Trauma is a leading cause of mortality and disability in children worldwide. The World Health Organization reports that 95% of all childhood injury deaths occur in Low-Middle-Income Countries (LMIC). Injury scores have been developed to facilitate risk stratification, clinical decision making, and research. Trauma registries in LMIC depend on adapted trauma scores that do not rely on investigations that require unavailable material or human resources. We sought to review and assess the existing trauma scores used in pediatric patients. Our objective is to determine their wideness of use, validity, setting of use, outcome measures, and criticisms. We believe that there is a need for an adapted trauma score developed specifically for pediatric patients in low-resource settings.

MATERIALS AND METHODS

A systematic review of the literature was conducted to identify and compare existing injury scores used in pediatric patients. We constructed a search strategy in collaboration with a senior hospital librarian. Multiple databases were searched, including Embase, Medline, and the Cochrane Central Register of Controlled Trials. Articles were selected based on predefined inclusion criteria by two reviewers and underwent qualitative analysis.

RESULTS

The scores identified are suboptimal for use in pediatric patients in low-resource settings due to various factors, including reliance on precise anatomic diagnosis, physiologic parameters maladapted to pediatric patients, or laboratory data with inconsistent accessibility in LMIC.

CONCLUSION

An important gap exists in our ability to simply and reliably estimate injury severity in pediatric patients and predict their associated probability of outcomes in settings, where resources are limited. An ideal score should be easy to calculate using point-of-care data that are readily available in LMIC, and can be easily adapted to the specific physiologic variations of different age groups.

The BIG Score and Prediction of Mortality in Pediatric Blunt Trauma

OBJECTIVES

To examine the association between in-hospital mortality and the BIG (composed of the base deficit [B], International normalized ratio [I], Glasgow Coma Scale [G]) score measured on arrival to the emergency department in pediatric blunt trauma patients, adjusted for pre-hospital intubation, volume administration, and presence of hypotension and head injury. We also examined the association between the BIG score and mortality in patients requiring admission to the intensive care unit (ICU).

STUDY DESIGN

A retrospective 2001-2012 trauma database review of patients with blunt trauma ≤ 17 years old with an Injury Severity score ≥ 12. Charts were reviewed for in-hospital mortality, components of the BIG score upon arrival to the emergency department, prehospital intubation, crystalloids ≥ 20 mL/kg, presence of hypotension, head injury, and disposition.

RESULTS

50/621 (8%) of the study patients died. Independent mortality predictors were the BIG score (OR 11, 95% CI 6-25), prior fluid bolus (OR 3, 95% CI 1.3-9), and prior intubation (OR 8, 95% CI 2-40). The area under the receiver operating characteristic curve was 0.95 (CI 0.93-0.98), with the optimal BIG cutoff of 16. With BIG <16, death rate was 3/496 (0.006, 95% CI 0.001-0.007) vs 47/125 (0.38, 95% CI 0.15-0.7) with BIG ≥ 16, (P < .0001). In patients requiring admission to the ICU, the BIG score remained predictive of mortality (OR 14.3, 95% CI 7.3-32, P < .0001).

CONCLUSIONS

The BIG score accurately predicts mortality in a population of North American pediatric patients with blunt trauma independent of pre-hospital interventions, presence of head injury, and hypotension, and identifies children with a high probability of survival (BIG <16). The BIG score is also associated with mortality in pediatric patients with trauma requiring admission to the ICU.

Mortality Risk in Pediatric Motor Vehicle Crash Occupants: Accounting for Developmental Stage and Challenging Abbreviated Injury Scale Metrics

OBJECTIVE

Survival risk ratios (SRRs) and their probabilistic counterpart, mortality risk ratios (MRRs), have been shown to be at odds with Abbreviated Injury Scale (AIS) severity scores for particular injuries in adults. SRRs have been validated for pediatrics but have not been studied within the context of pediatric age stratifications. We hypothesized that children with similar motor vehicle crash (MVC) injuries may have different mortality risks (MR) based upon developmental stage and that these MRs may not correlate with AIS severity.

METHODS

The NASS-CDS 2000-2011 was used to define the top 95% most common AIS 2+ injuries among MVC occupants in 4 age groups: 0-4, 5-9, 10-14, and 15-18 years. Next, the National Trauma Databank 2002-2011 was used to calculate the MR (proportion of those dying with an injury to those sustaining the injury) and the co-injury-adjusted MR (MRMAIS) for each injury within 6 age groups: 0-4, 5-9, 10-14, 15-18, 0-18, and 19+ years. MR differences were evaluated between age groups aggregately, between age groups based upon anatomic injury patterns and between age groups on an individual injury level using nonparametric Wilcoxon tests and chi-square or Fisher's exact tests as appropriate. Correlation between AIS and MR within each age group was also evaluated.

RESULTS

MR and MRMAIS distributions of the most common AIS 2+ injuries were right skewed. Aggregate MR of these most common injuries varied between the age groups, with 5- to 9-year-old and 10- to 14-year-old children having the lowest MRs and 0- to 4-year-old and 15- to 18-year-old children and adults having the highest MRs (all P <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MRMAIS ranging from 0 to 6% and 0 to 4.5%, respectively. Injuries to particular body regions also varied with respect to MR based upon age. For example, thoracic injuries in adults had significantly higher MRMAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (P =.04; P <.01). Furthermore, though AIS was positively correlated with MR within each age group, less correlation was seen for children than for adults. Large MR variations were seen within each AIS grade, with some lower AIS severity injuries demonstrating greater MRs than higher AIS severity injuries. As an example, MRMAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture.

CONCLUSIONS

Trauma severity metrics are important for outcome prediction models and can be used in pediatric triage algorithms and other injury research. Trauma severity may vary for similar injuries based upon developmental stage, and this difference should be reflected in severity metrics. The MR-based data-driven determination of injury severity in pediatric occupants of different age cohorts provides a supplement or an alternative to AIS severity classification for pediatric occupants in MVCs.

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.

Factors associated with the use of cervical spine computed tomography imaging in pediatric trauma patients

OBJECTIVES

The objectives were to identify patient and hospital characteristics associated with the use of computed tomography (CT) imaging of the cervical spine (c-spine) in the evaluation of injured children and, in particular, to examine the influence of hospital setting.

METHODS

This was a retrospective cohort of children younger than 19 years of age from the Massachusetts Hospital Emergency Department (ED) database who were discharged from the ED with an injury diagnosis from 2005 through 2009. Multivariable logistic regression was used to analyze characteristics associated with CT imaging of the c-spine.

RESULTS

Of the 929,626 pediatric patients diagnosed with an injury in Massachusetts EDs and then discharged home, 1.3% underwent CT imaging of the c-spine. Rates of CT imaging nearly doubled over the 5 years. In the multivariable model, patient age (adjusted odds ratio [AOR] = 2.3, 95% confidence interval [CI] = 2.0 to 2.7 for children age 12 to 18 years vs. under 1 year of age) and evaluation outside of a pediatric Level I trauma center (AOR = 2.2, 95% CI = 1.1 to 4.3 for children evaluated at non Level I trauma centers vs. pediatric Level I trauma centers; AOR = 2.1, 95% CI = 0.93 to 4.7 for children evaluated at adult Level I trauma centers vs. pediatric Level I trauma centers) were associated with higher rates of CT imaging of the c-spine.

CONCLUSIONS

Cervical spine CT imaging for children discharged from the ED with trauma diagnoses increased from 2005 through 2009. Older age and evaluation outside a Level I pediatric trauma center were associated with a higher c-spine CT rate. Educational interventions focused outside pediatric trauma centers may be an effective approach to decreasing CT imaging of the c-spine of pediatric trauma patients.

Pediatric trauma BIG score: predicting mortality in children after military and civilian trauma

OBJECTIVE

To develop a validated mortality prediction score for children with traumatic injuries.

PATIENTS AND METHODS

We identified all children (<18 years of age) in the US military established Joint Theater Trauma Registry from 2002 to 2009 who were admitted to combat-support hospitals with traumatic injuries in Iraq and Afghanistan. We identified factors associated with mortality using univariate and then multivariate regression modeling. The developed mortality prediction score was then validated on a data set of pediatric patients (≤ 18 years of age) from the German Trauma Registry, 2002-2007.

RESULTS

Admission base deficit, international normalized ratio, and Glasgow Coma Scale were independently associated with mortality in 707 patients from the derivation set and 1101 patients in the validation set. These variables were combined into the pediatric "BIG" score (base deficit + [2.5 × international normalized ratio] + [15 - Glasgow Coma Scale), which were each calculated to have an area under the curve of 0.89 (95% confidence interval: 0.83-0.95) and 0.89 (95% confidence interval: 0.87-0.92) on the derivation and validation sets, respectively.

CONCLUSIONS

The pediatric trauma BIG score is a simple method that can be performed rapidly on admission to evaluate severity of illness and predict mortality in children with traumatic injuries. The score has been shown to be accurate in both penetrating-injury and blunt-injury populations and may have significant utility in comparing severity of injury in future pediatric trauma research and quality-assurance studies. In addition, this score may be used to determine inclusion criteria on admission for prospective studies when accurately estimating the mortality for sample size calculation is required.

Prediction of pediatric death in the year after hospitalization: a population-level retrospective cohort study

BACKGROUND

The study of how the quality of pediatric end-of-life care varies across systems of health care delivery and financing is hampered by lack of methods to adjust for the probability of death in populations of ill children.

OBJECTIVE

To develop a prognostication models using administratively available data to predict the probability of in-hospital and 1-year postdischarge death.

METHODS

Retrospective cohort study of 0-21 year old patients admitted to Pennsylvania hospitals from 1994-2001 and followed for 1-year postdischarge mortality, assessing logistic regression models ability to predict in-hospital and 1-year postdischarge deaths.

RESULTS

Among 678,365 subjects there were 2,202 deaths that occurred during the hospitalization (0.32% of cohort) and 860 deaths that occurred 365 days or less after hospital discharge (0.13% of cohort). The model predicting hospitalization deaths exhibited a C statistic of 0.91, with sensitivity of 65.9% and specificity of 92.9% at the 99th percentile cutpoint; while the model predicting 1-year postdischarge deaths exhibited a C statistic of 0.92, with sensitivity of 56.1% and specificity of 98.4% at the 99th percentile cutpoint.

CONCLUSIONS

Population-level mortality prognostication of hospitalized children using administratively available data is feasible, assisting the comparison of health care services delivered to children with the highest probability of dying during and after a hospital admission.

Comparison of the new injury severity score and the injury severity score in multiple trauma patients

OBJECTIVE

To assess whether these characteristics of less misclassification and greater area under receiver operator characteristic (ROC) curve of the new injury severity score (NISS) are better than the injury severity score (ISS) as applying it to our multiple trauma patients registered into the emergency intensive care unit (EICU).

METHODS

This was a retrospective review of registry data from 2 286 multiple trauma patients consecutively registered into the EICU from January 1,1997 to December 31, 2006 in the Second Affiliated Hospital, Medical School of Zhejiang University in China. Comparisons between ISS and NISS were made using misclassification rates, ROC curve analysis, and the H-L statistics by univariate and multivariate logistic progression model.

RESULTS

Among the 2 286 patients, 176 (7.7%) were excluded because of deaths on arrival or patients less than 16 years of age. The study population therefore comprised 2 110 patients. Mean EICU length of stay (LOS) was 7.8 days ?2.4 days. Compared with the blunt injury group, the penetrating injury group had a higher percentage of male, lower mean EICU LOS and age. The most frequently injured body regions were extremities and head/neck, followed by thorax, face and abdomen in the blunt injury group; whereas, thorax and abdomen were more frequently seen in the penetrating injury group. The minimum misclassification rate for NISS was slightly less than ISS in all groups (4.01% versus 4.49%). However, NISS had more tendency to misclassify in the penetrating injury group. This, we noted, was attributed mainly to a higher false-positive rate (21.04% versus 15.55% for ISS, t equal to 3.310, P less than 0.001), resulting in an overall misclassification rate of 23.57% for NISS versus 18.79% for ISS (t equal to 3.290, P less than 0.001). In the whole sample, NISS presented equivalent discrimination (area under ROC curve: NISS equal to 0.938 versus ISS equal to 0.943). The H-L statistics showed poorer calibration (48.64 versus 32.11, t equal to 3.305, P less than 0.001) in the penetrating injury group.

CONCLUSIONS

NISS should not replace ISS because they share similar accuracy and calibration in predicting multiple blunt trauma patients. NISS may be more sensitive but less specific than ISS in predicting mortality in certain penetrating injury patients.

Ten years of new injury severity score (NISS): is it a possible change?

The article is a bibliographic review which intends to present the actual range of researches comparing the Injury Severity Score (ISS) and the New Injury Severity Score (NISS). Databases were searched using the keyword NISS, with 42 articles, 23 of which didn't compare the two indexes. Most part of the 19 selected articles showed that NISS has been more accurate in predicting the outcomes (dependent variables) than ISS, moreover in severe and specific trauma. Studies with populations between 1,000 and 10,000 resulted in NISS-favorable results, whereas studies with populations larger than 10,000 or smaller than 1,000 showed either NISS-favorable results or no difference between the two groups. However, there were no studies showing ISS-favorable results. These results and the easier calculation of NISS lead to a future replacement of ISS by NISS.

The evolution of trauma services at Beaumont Hospital

OBJECTIVE

To review and examine the epidemiology, severity and management of trauma admissions at the national neurosurgical teaching hospital.

METHODS

An extensive audit of volume, type and severity of injury and the management requirements of the trauma population admitted to the hospital.

RESULTS

The vast majority of severely injured patients were referred from outside the catchment area of the hospital with only 26% being admitted directly through the Emergency Department. As a consequence, 73% of patients arrived out of normal working hours, which posed problems in providing skilled trauma specialists.

CONCLUSIONS

The management of patients with serious injury is complex. The large proportion of patients with critical injuries, some of whom were paediatric, highlighted the need for 24 h cover by senior trauma personnel and the provision of radiology and operating facilities to meet their needs. The inclusion of indicators of alterations in innate or adaptive immune responses may improve the predictive power of severity of injury scores.

Analysis of management of patients with multiple injuries of the locomotor system

Body injuries are very serious problems in industrialised countries and they are frequent causes of fatalities in our times. The variety and multiple combinations of body injuries are a challenge for the trauma team. On the basis of clinical and radiological documentation 315 patients with multiple injuries of the locomotor system (MILS) were included in the study. The criterion for inclusion of the patients into the study group was identification of MILS. The study showed that these injuries often involve young people (53%) (predominantly men) aged between 16 and 45 years. Road accidents were the most frequent cause of injuries -80.6%. MILS affected the lower limb in 49.,4%, upper limb in 33.2% and pelvis in 14.1%; 75% of the patients studied also suffered from concomitant injuries. The head and brain were involved in 92.9%, chest in 31.5% and abdomen in 21.3%. The mortality index for the population studied was 14%. An increasing value of the Injury Severity Score (ISS) or New Injury Severity Score (NISS) caused delay in surgical management of bone injuries and correlated with prolonged hospitalisation. Analysis emphasised the usefulness of the NISS as a valuable prognostic instrument in assessment of severity of injuries in patients with multiple injuries of the locomotor system.

Childhood falls: characteristics, outcome, and comparison of the Injury Severity Score and New Injury Severity Score

OBJECTIVES

The aim of this study was to determine the general characteristics of childhood falls, factors affecting on mortality, and to compare the Injury Severity Score (ISS) and the New Injury Severity Score (NISS) as predictors of mortality and length of hospital stay in childhood falls.

METHODS

We retrospectively analysed over a period of 8 years children aged younger than14 years who had sustained falls and who were admitted to our emergency department. Data on the patients' age, sex, type of fall, height fallen, arrival type, type of injuries, scoring systems, and outcome were investigated retrospectively. The ISS and NISS were calculated for each patient. Comparisons between ISS and NISS for prediction of mortality were made by receiver operating characteristic (ROC) curve and Hosmer-Lemeshow (HL) goodness of fit statistics.

RESULTS

In total, there were 2061 paediatric trauma patients. Falls comprised 36 (n = 749) of these admissions. There were 479 male and 270 female patients. The mean (SD) age was 5.01 (3.48) years, and height fallen was 3.8 (3) metres. Over half (56.6%) of patients were referred by other centres. The most common type of fall was from balconies (38.5%), and head trauma was the most common injury (50%). The overall mortality rate was 3.6%. The cut off value for both the ISS and NISS in predicting mortality was 22 (sensitivity 90.5%, specificity 95.4% for ISS; sensitivity 100%, specificity 88.7% for NISS) (p>0.05). Significant factors affecting mortality in logistic regression analysis were Glasgow Coma Scale (GCS) <9, ISS >22, and NISS >22. There were no significant differences in ROC between three scoring systems. The HL statistic showed poorer calibration (p = 0.02 v p = 0.37, respectively) of the NISS compared with the ISS.

CONCLUSIONS

In our series, the head was the most frequent site of injury, and the most common type of fall was from balconies. Scores on the GCS, NISS, and ISS are significantly associated with mortality. The performance of the NISS and ISS in predicting mortality in childhood falls was similar.

Which AIS Based Scoring System is the Best Predictor of Outcome in Orthopaedic Blunt Trauma Patients?

BACKGROUND

Abbreviated Injury Scale (AIS)-based systems-the Injury Severity Score (ISS), New Injury Severity Score (NISS), and AISmax-are used to assess trauma patients. The merits of each in predicting outcome are controversial.

METHODS

A large prospective database was used to assess their predictive capacity using receiver operator characteristic curves.

RESULTS

In all, 10,062 adult, blunt-trauma patients met the inclusion criteria. All systems were significant outcome predictors for sepsis, multiple organ failure (MOF), length of hospital stay, length of intensive care unit (ICU) admission and mortality (p < 0.0001). NISS was a significantly better predictor than the ISS for mortality (p < 0.0001). NISS was equivalent to the AISmax for mortality prediction and superior in patients with orthopaedic injuries. NISS was significantly better for sepsis, MOF, ICU stay, and total hospital stay (p < 0.0001).

CONCLUSIONS

NISS is superior or equivalent to the ISS and AISmax for prediction of all investigated outcomes in a population of blunt trauma patients. As NISS is easier to calculate, its use is recommended to stratify patients for clinical and research purposes.

Prediction of Outcomes in Trauma: Anatomic or Physiologic Parameters?

BACKGROUND

Prediction of outcomes after injury has traditionally incorporated measures of injury severity, but recent studies suggest that including physiologic and shock measures can improve accuracy of anatomic-based models. A recent single-institution study described a mortality predictive equation [f(x) = 3.48 - .22 (GCS) - .08 (BE) + .08 (Tx) + .05 (ISS) + .04 (Age)], where GSC is Glasgow Coma Score, BE is base excess, Tx is transfusion requirement, and ISS is Injury Severity Score, which had 63% sensitivity, 94% specificity, (receiver operating characteristic [ROC] 0.96), but did not provide comparative data for other models. We have previously documented that the Physiologic Trauma Score, including only physiologic variables (systemic inflammatory response syndrome, Glasgow Coma Score, age) also accurately predicts mortality in trauma. The objective of this study was to compare the predictive abilities of these statistical models in trauma outcomes.

METHODS

Area under the ROC curve of sensitivity versus 1-specificity was used to assess predictive ability and measured discrimination of the models.

RESULTS

The study cohort consisted of 15,534 trauma patients (80% blunt mechanism) admitted to a Level I trauma center over a 3-year period (mean age 37 +/- 18 years; mean Injury Severity Score 10 +/- 10; mortality 4%). Sensitivity of the new predictive model was 45%, specificity was 96%, ROC was 0.91, validating this new trauma outcomes model in our institution. This was comparable with area under the ROC for Revised Trauma Score (ROC 0.88), Trauma and Injury Severity Score (ROC 0.97), and Physiologic Trauma Score (ROC 0.95), but superior compared with admission Glasgow Coma Score (ROC 0.79), Injury Severity Score (ROC 0.79), and age (ROC 0.60).

CONCLUSIONS

The predictive ability of this new model is superior to anatomic-based models such as Injury Severity Score, but comparable with other physiologic-based models such as Revised Trauma Score, Physiologic Trauma Score and Trauma, and Injury Severity Score.

Functional status after childhood traumatic brain injury

BACKGROUND

Identification of children after traumatic brain injury (TBI) likely to have functional deficits at trauma center discharge will facilitate care.

METHODS

Two logistic regression models were derived from data on 4,439 children after TBI 7 to 14 years old enrolled in the National Pediatric Trauma Registry between 1994 and 2001 to predict physical and cognitive disabilities.

RESULTS

Children with open or multiple fractures or closed fractures or injured by motor vehicles were 8.2, 3.5, or 2.5 times more likely, respectively, than those without those circumstances to have discharge physical disabilities. Likelihood of cognitive impairment was increased by factors of 3.2 and 5.8 in children obtunded or comatose on arrival. Preexisting cognitive deficits, injury severity, and intubation predicted physical and cognitive disabilities. The C statistic was 0.862 for the motor model and 0.860 for the cognitive model.

CONCLUSION

Predicting the likelihood of morbidity after acute management of childhood TBI can provide information pertinent to providing effective care.

The Injury Severity Score or the New Injury Severity Score for predicting intensive care unit admission and hospital length of stay?

OBJECTIVES

To compare the New Injury Severity Score (NISS) and the Injury Severity Score (ISS) as predictors of intensive care unit (ICU) admission and hospital length of stay (LOS) in an urban North American trauma population and in a subset of patients with head injuries.

METHODS

The study population consisted of 23,909 patients from three urban level I trauma centres in the province of Quebec, Canada. The predictive accuracies of the NISS and the ISS were compared using Receiver Operator Characteristic (ROC) curves and Hosmer-Lemeshow (H-L) statistics for the logistic regression model of ICU admission and using r2 for the linear regression model of LOS.

RESULTS

A total of 7660 (32%) patients were admitted to the ICU. Mean LOS was 8.2+/-2.5 days. In the whole sample, the NISS presented equivalent discrimination (area under ROC curve: NISS = 0.839 versus ISS = 0.843, p = 0.08) but better calibration (H-L statistic: 309 versus 611) for predicting ICU admission. In the subgroup patients with moderate to serious head injuries, the NISS was a better predictor of ICU admission in terms of both discrimination (area under ROC curve: NISS = 0.771 versus ISS = 0.747, p < 0.00001) and calibration (H-L statistic: 12 versus 21). The NISS explained more variation in LOS than the ISS for the whole sample (r2 = 0.254 versus 0.249, p = 0.0008) and in the sub-population with moderate to severe head injuries (r2 = 0.281 versus 0.263, p = 0.0002).

CONCLUSIONS

The NISS is a better choice for case mix control in trauma research than the ISS for predicting ICU admission and LOS, particularly among patients with moderate to severe head injuries.

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.

The New Injury Severity Score: a more accurate predictor of in-hospital mortality than the Injury Severity Score

OBJECTIVE

The purpose of this study was to determine whether the New Injury Severity Score (NISS) is a better predictor of mortality than the Injury Severity Score (ISS) in general and in subgroups according to age, penetrating trauma, and body region injured.

METHODS

The study population consisted of 24,263 patients from three urban Level I trauma centers in the province of Quebec, Canada. Discrimination and calibration of NISS and ISS models were compared using receiver operator characteristic (ROC) curves and Hosmer-Lemeshow statistics.

RESULTS

NISS showed better discrimination than ISS (area under the ROC curve = 0.827 vs. 0.819; p = 0.0006) and improved calibration (Hosmer-Leme-show = 62 vs. 112). The advantage of the NISS over the ISS was particularly evident among patients with head/neck injuries (area under the ROC curve = 0.819 vs. 0.784; p < 0.0001; Hosmer-Lemeshow = 59 vs. 350).

CONCLUSION

The NISS is a more accurate predictor of in-hospital death than the ISS and should be chosen over the ISS for case-mix control in trauma research, especially in certain subpopulations such as head/neck-injured patients.

Comparison of the New Injury Severity Score and the Injury Severity Score

BACKGROUND

The New Injury Severity Score (NISS) was proposed in 1997 to replace the Injury Severity Score (ISS) because it is more sensitive for mortality. We aim to test whether this is true in our patients.

METHODS

This study was a retrospective review of data from 6,231 consecutive patients over 3 years in the trauma registry of a Level I trauma center studying outcome, ISS, and NISS.

RESULTS

Misclassification rates were 3.97% for the NISS and 4.35% for the ISS. The receiver operating characteristic curve areas were 0.936 and 0.94, respectively. Neither the ISS nor the NISS were well calibrated (Hosmer-Lemeshow statistic, 36.11 and 49.28, respectively; p < 0.001).

CONCLUSION

The NISS should not replace the ISS, as they share similar accuracy and calibration.

Prediction of Mortality in Pediatric Trauma Patients: New Injury Severity Score Outperforms Injury Severity Score in the Severely Injured

BACKGROUND

The Injury Severity Score (ISS) is a widely accepted method of measuring severity of traumatic injury. A modification has been proposed--the New Injury Severity Score (NISS). This has been shown to predict mortality better in adult trauma patients, but it had no predictive benefit in pediatric patients. The aim of this study was to determine whether the NISS outperforms the ISS in a large pediatric trauma population.

METHODS

Admissions in the National Pediatric Trauma Registry between April 1996 and September 1999 were included. The ISS and NISS were calculated for each patient. The study endpoints were mortality at hospital discharge, functional outcome in three domains (expression, locomotion, and feeding), and discharge disposition for the survivors. Predictive ability of each score was assessed by area under the receiver operating characteristic curve.

RESULTS

The NISS and ISS performed equally well at predicting mortality in patients with lower injury severity (ISS < 25), but the NISS was significantly better at predicting mortality in the more severely injured patients. Both scores performed equally well at predicting expression and feeding ability. The NISS was superior to the ISS in predicting locomotion ability at discharge. Thirty-seven percent of patients had an NISS that was higher than their ISS. These patients had a significantly higher mortality and suffered worse functional outcomes.

CONCLUSION

The NISS performs as well as the ISS in pediatric patients with lower injury severity and outperforms the ISS in those with higher injury severity.

Chapter Five: Functions, Requirements, Supplies, Damage, and Needs

This Chapter describes methods for defining the level of damage from an event, its impact on the functional status of the affected society, and for identifying the needs that result from the damage. The event may produce damage to the population (injuries, death), its constructions and societal functions, and/or to the environment. Societal functions are described as production functions with inputs, transformations, consumption of resources, and outputs. Distinction between available supplies, requirements, and needs is stressed. The differences between damage assessments and needs assessments are described. Needs for goods and services that are greater than the available level of supplies produces deficits. The concept of thresholds of available resources required to maintain the pre-event functional state, those necessary to sustain basic functional states, and those required for survival is developed. Surplus of available supplies is subdivided into those needed for contingencies and those that comprise luxuries. Indicators are required that define either the level of function or the level of available supplies.Distribution of available supplies (who receives them) impacts whether critical and functional requirements of a population, or part of the affected population, are satisfied.When critical requirements are not met, the crude mortality rate increases. Severity scoring of the damage sustained and the effects of responses is described. All damage and needs assessments and responses to them relate to the pre-event state of the affected society, and the objective of disaster responses is to return the affected society to its pre-event functional state.

Triage scoring systems, severity of illness measures, and mortality prediction models in pediatric trauma

Trauma triage scores, severity of illness measures, and mortality prediction models quantitate severity of injury and stratify patients according to a specified outcome. Triage scoring systems are typically used to assist prehospital personnel determine which patients require trauma center care, but they are not recommended as the sole determinant of triage. Severity of illness measures and mortality prediction models are used in clinical and health services research for risk-adjusted outcomes analyses and institutional benchmarking. As clinicians and researchers, it is imperative that we be knowledgeable of the methodologies and applications of these scoring and risk prediction systems to ensure their quality and appropriate utilization.