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

ABSTRACT

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.