The Bidirectionality of Global Surgical Research: The Utility of the Malawi Trauma Score in the United States Trauma Population.

INTRODUCTION: Trauma scoring systems provide valuable risk stratification of injured patients. Trauma scoring systems developed in resource-limited settings, such as the Malawi Trauma Score (MTS), are based on readily available clinical information. This study sought to test the performance of the MTS in a United States trauma population. MATERIALS AND METHODS: We analyzed the United States National Trauma Data Bank during 2017-2020. MTS uses alertness score: alert, responds to verbal or painful stimuli, or unresponsive (AVPU), age, sex, presence of a radial pulse, and primary anatomic injury location. MTS and an age-adjusted version reflective of the US age distribution, was evaluated for its performance in predicting crude mortality in the National Trauma Data Bank using receiver operating characteristic analysis. We utilized logistic regression to model the odds ratio of death at a particular MTS cutoff. RESULTS: A total of 3,833,929 patients were included. The mean age was 49.3 y (sandard deviation 24.4), with a male preponderance (61.1%). Crude mortality was 3.4% (n = 131,452/3,833,929). The area under the curve for the MTS in predicting mortality was 0.87 (95% CI 0.87, 0.88). The area under the curve for a cutoff of 15 was 0.83 (95% CI 0.83, 0.83). An MTS of 15 higher had an odds ratio of death of 46.5 (95% CI 45.9, 47.1), compared to those with a score of 14 or lower. CONCLUSIONS: MTS has excellent performance as a predictor of mortality in a US trauma population. MTS is simple to calculate and can be estimated in the prehospital setting or the emergency department. Consequently, it may have utility as a triage tool in both high-income trauma systems and resource-limited settings.

Validation of age-specific survival prediction in pediatric patients with blunt trauma using trauma and injury severity score methodology: a ten-year Nationwide observational study.

BACKGROUND: In-hospital mortality in trauma patients has decreased recently owing to improved trauma injury prevention systems. However, no study has evaluated the validity of the Trauma and Injury Severity Score (TRISS) in pediatric patients by a detailed classification of patients' age and injury severity in Japan. This retrospective nationwide study evaluated the validity of TRISS in predicting survival in Japanese pediatric patients with blunt trauma by age and injury severity. METHODS: Data were obtained from the Japan Trauma Data Bank during 2009-2018. The outcomes were as follows: (1) patients' characteristics and mortality by age groups (neonates/infants aged 0 years, preschool children aged 1-5 years, schoolchildren aged 6-11 years, and adolescents aged 12-18 years), (2) validity of survival probability (Ps) assessed using the TRISS methodology by the four age groups and six Ps-interval groups (0.00-0.25, 0.26-0.50, 0.51-0.75, 0.76-0.90, 0.91-0.95, and 0.96-1.00), and (3) the observed/expected survivor ratio by age- and Ps-interval groups. The validity of TRISS was evaluated by the predictive ability of the TRISS method using the receiver operating characteristic (ROC) curves that present the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the receiver operator characteristic curve (AUC) of TRISS. RESULTS: In all the age categories considered, the AUC for TRISS demonstrated high performance (0.935, 0.981, 0.979, and 0.977). The AUC for TRISS was 0.865, 0.585, 0.614, 0.585, 0.591, and 0.600 in Ps-interval groups (0.96-1.00), (0.91-0.95), (0.76. - 0.90), (0.51-0.75), (0.26-0.50), and (0.00-0.25), respectively. In all the age categories considered, the observed survivors among patients with Ps interval (0.00-0.25) were 1.5 times or more than the expected survivors calculated using the TRISS method. CONCLUSIONS: The TRISS methodology appears to predict survival accurately in Japanese pediatric patients with blunt trauma; however, there were several problems in adopting the TRISS methodology for younger blunt trauma patients with higher injury severity. In the next step, it may be necessary to develop a simple, high-quality prediction model that is more suitable for pediatric trauma patients than the current TRISS model.

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.

Use of neural network based on international classification ICD-10 in patients with head and neck injuries in Lublin Province, Poland, between 2006-2018, as a predictive value of the outcomes of injury sustained.

INTRODUCTION AND OBJECTIVE: Head and neck injuries are a heterogeneous group in terms of both clinical course and prognosis. For years, there have been attempts to create an ideal tool to predict the outcomes and severity of injuries. The aim of this study was evaluation of the use of selected artificial intelligence methods for outcome predictions of head and neck injuries. MATERIAL AND METHODS: 6,824 consecutive cases of patients who sustained head and neck injuries, treated in hospitals in the Lublin Province between 2006-2018, whose data was provided by National Institute of Public Health / National Institute of Hygiene, were analyzed retrospectively. Patients were qualified using International Statistical Classification of Diseases and Related Health Problems (10th Revision). The multilayer perceptron (MLP) structure was utilized in numerical studies. Neural network training was achieved with the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. RESULTS: In the designed network, the highest classification efficiency was obtained for the group of deaths (80.7%). The average value of correct classifications for all analyzed cases was 66%. The most important variable influencing the prognosis of an injured patient was diagnosis (weight 1.929). Gender and age were variables of less significance with weight 1.08 and 1.073, respectively. CONCLUSIONS: Designing a neural network was hindered due to the large amount of cases and linking of a large number of deaths with specific diagnosis (S06). With a predictive value of 80.7% for mortality, ANN can be a promising tool in the future; however, additional variables should be introduced into the algorithm to increase the predictive value of the network. Further studies, including other types of injuries and additional variables, are needed to introduce this method into clinical use.

Validation of the Conventional Trauma and Injury Severity Score and a Newly Developed Survival Predictive Model in Pediatric Patients with Blunt Trauma: A Nationwide Observation Study.

To date, there is no clinically useful prediction model that is suitable for Japanese pediatric trauma patients. Herein, this study aimed to developed a model for predicting the survival of Japanese pediatric patients with blunt trauma and compare its validity with that of the conventional TRISS model. Patients registered in the Japan Trauma Data Bank were grouped into a derivation cohort (2009-2013) and validation cohort (2014-2018). Logistic regression analysis was performed using the derivation dataset to establish prediction models using age, injury severity, and physiology. The validity of the modified model was evaluated by the area under the receiver operating characteristic curve (AUC). Among 11 predictor models, Model 1 and Model 11 had the best performance (AUC = 0.980). The AUC of all models was lower in patients with survival probability Ps < 0.5 than in patients with Ps ≥ 0.5. The AUC of all models was lower in neonates/infants than in other age categories. Model 11 also had the best performance (AUC = 0.762 and 0.909, respectively) in patients with Ps < 0.5 and neonates/infants. The predictive ability of the newly modified models was not superior to that of the current TRISS model. Our results may be useful to develop a highly accurate prediction model based on the new predictive variables and cutoff values associated with the survival mortality of injured Japanese pediatric patients who are younger and more severely injured by using a nationwide dataset with fewer missing data and added valuables, which can be used to evaluate the age-related physiological and anatomical severity of injured patients.

Validation of the trauma mortality prediction scores from a Malaysian population.

BACKGROUND: Well-known trauma mortality prediction scores such as New Injury Severity Score (NISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) have been externally validated from high-income countries with established trauma databases. However, these scores were never used in Malaysian population. In this current study, we attempted to validate these scoring systems using our regional trauma surgery database. METHODS: A retrospective analysis of the regional Malaysian Trauma Surgery Database was performed over a period of 3 years from May 2011 to April 2014. NISS, RTS, Major Trauma Outcome Study (MTOS)-TRISS, and National Trauma Database (NTrD)-TRISS scores were recorded and calculated. Individual scoring system's performance in predicting trauma mortality was compared by calculating the area under the receiver operating characteristic (AUC) curve. Youden index and associated optimal cutoff values for each scoring system was calculated to predict mortality. The corresponding positive predictive value, negative predictive value, and accuracy of the cutoff values were calculated. RESULTS: A total of 2208 trauma patients (2004 blunt and 204 penetrating injuries) with mean age of 36 (SD = 16) years were included. There were 239 deaths with a corresponding mortality rate of 10.8%. The AUC calculated for the NISS, RTS, MTOS-TRISS, and NTrD-TRISS were 0.878, 0.802, 0.812, and 0.848, respectively. The NISS score with a cutoff value of 24, sensitivity of 86.6% and specificity of 74.3%, outperformed the rest (p < 0.001). Mortality was predicted by NISS with an overall accuracy of 75.6%; its positive predictive value was at 29.02% and negative predictive value at 97.86%. CONCLUSION: Amongst the four scores, the NISS score is the best trauma mortality prediction model suited for a local Malaysian trauma population. Further validation with multicentre data in the country may require to ascertain the finding.

Constructing a trauma scoring system from databases of road crash patients in Philippine Hospitals (2009–2019)

Introduction@#Trauma scoring standardizes the severity of injuries of patients brought to trauma centers and is predictive of the outcome or prognosis among trauma victims. Hence, creating a trauma score allows for proper prioritization as well as proper management of patients in the emergency departments. @*Objectives@#The objective of the study is to come up with a trauma scoring system that correlates to the probability of survival of a patient using the patient databases in major hospitals in the Philippines representing the three major island groups, Luzon, Visayas, and Mindanao. The study will also compare this proposed trauma scoring system with the gold standard (Revised Trauma Score) developed by Champion in 1989. @*Methods@#The proposed Philippine Trauma Scoring System (PTSS) was based on data from the eight largest tertiary hospitals catering to trauma patients. A total of 40,286 patient charts were reviewed. The proposed trauma scoring system integrates concepts used in the Revised Trauma Score (RTS), with addition of age (from Kampala Trauma Scoring), as well as the Injury Score (based on the number of body parts injured). This proposed scoring system was weighted, using logistic regression to come up with coefficients for the components of the PTSS for a more accurate prediction of patient survival. The Receiver Operating Characteristic (ROC) was used to plot Sensitivity vs. 1-Specificity. In this analysis, ROC was used to evaluate and compare how good the models are in predicting patient recovery.@*Results@#The components of GCS, RR, SBP, age, and body parts injured were significant predictors of patient outcomes for patients with trauma, specifically the road crash patients in this Philippine study. This study showed that both the PTSS and RTS have a significantly greater area under the curve than the diagonal reference line, which means that both the scoring system have a significant predictive value. The best predictive value, however, comes from the proposed scoring system that is developed from this study in the Philippines. Compared to the gold standard, PTSS Model 1 is a better predictor of outcomes than the gold standard RTS (ROC-AUC = 0.659 vs. 0.633) using only 22,214 valid subject population that contained all the variables needed for the PTSS analysis. @*Conclusion@#In a developing country like the Philippines, there are limited resources especially in the healthcare setting. Therefore, it is important to lessen errors in triaging which may result in resource waste and a higher risk of adverse outcomes for the patients. Thus, the PTSS developed in this study can be used by Philippine hospitals as it is uniquely based on Filipino patients using a large database representative of the eight largest tertiary hospitals in the Philippines. The proposed PTSS is shown in this study as the best classifier for patient outcome compared to the gold standard – RTS of Champion.

Correlation Analysis of Trauma Scoring System in Predictive Validity in Motor Vehicle Accident

PURPOSE: The Trauma Scoring System is used for triage and treatment decision-making of injured patients. An ideal scoring system should have predictive validity, correlate with outcome, be easily applicable, and be reliably applied among observations. The purpose of this study was to analysis the trauma scoring system to predict motor vehicle accident (MVA) survival and mortality. METHODS: The registry data of MVA trauma patients admitted to W hospital between October 2008 and December 2009 were retrospectively reviewed. The dependent variable of interest was patient survival (coded as live or die). The independent variables used in the study included the full term for ISS (ISS) derived using Abbreviated Injury Score (AIS) and body system maximum AIS scores, full term (ICISS) score, full term (RTS) and full term (TRISS). Survival predictability in each scoring system (ISS, RTS TRISS, ICISS and ICISS full model) was compared. RESULTS: Trauma severity scores of the 1,843 patients [1,163 males (63.1%), 680 females (36.9%); mean age 41.7+/-20.9 years] were: RTS 7.36+/-3.23 (median: 7.84), ISS 6.42+/-8.42 (median: 4), TRISS 0.952+/-0.153 (median: 0.994), ICISS 0.970+/-0.055 (median: 0.990), and ICISS full model 0.982+/-0.104 (median: 0.998). To analyze the predictive validity of the receiver operation characteristic (ROC) curve analysis, ISS 0.956, ICISS 0.522, ICISS full model 0.398, RTS 0.095, and TRISS 0.368 appeared to predict the validity of the widest area of the ROC curve area, with ISS being most reliable. CONCLUSION: ISS is the best predictor of survival than the other derived other scoring systems for MVA patients.