PurposeThe 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 MethodsOf 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.ResultsIn 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)].ConclusionThese 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.
Background: Injury severity scoring systems that quantify and predict trauma outcomes have not been established in Korea. This study was designed to determine the best system for use in the Korean trauma population. Methods: We collected and analyzed the data from trauma patients admitted to our institution from January 2010 to December 2014. Injury Severity Score (ISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) were calculated based on the data from the enrolled patients. Area under the receiver operating characteristic (ROC) curve (AUC) for the prediction ability of each scoring system was obtained, and a pairwise comparison of ROC curves was performed. Additionally, the cut-off values were estimated to predict mortality, and the corresponding accuracy, positive predictive value, and negative predictive value were obtained. Results: A total of 7,120 trauma patients (6,668 blunt and 452 penetrating injuries) were enrolled in this study. The AUCs of ISS, RTS, and TRISS were 0.866, 0.894, and 0.942, respectively, and the prediction ability of the TRISS was significantly better than the others (p < 0.001, respectively). The cut-off value of the TRISS was 0.9082, with a sensitivity of 81.9% and specificity of 92.0%; mortality was predicted with an accuracy of 91.2%; its positive predictive value was the highest at 46.8%. Conclusions:The results of our study were based on the data from one institution and suggest that the TRISS is the best prediction model of trauma outcomes in the current Korean population. Further study is needed with more data from multiple centers in Korea.
PurposeThis study aimed to determine the mortality rate in patients with severe trauma and the risk factors for trauma mortality based on 3 years' data in a regional trauma center in Korea.MethodsWe reviewed the medical records of severe trauma patients admitted to Ajou University Hospital with an Injury Severity Score (ISS) > 15 between January 2010 and December 2012. Pearson chi-square tests and Student t-tests were conducted to examine the differences between the survived and deceased groups. To identify factors associated with mortality after severe trauma, multivariate logistic regression was performed.ResultsThere were 915 (743 survived and 172 deceased) enrolled patients with overall mortality of 18.8%. Age, blunt trauma, systolic blood pressure (SBP) at admission, Glasgow Coma Scale (GCS) at admission, head or neck Abbreviated Injury Scale (AIS) score, and ISS were significantly different between the groups. Age by point increase (odds ratio [OR], 1.016; P = 0.001), SBP ≤ 90 mmHg (OR, 2.570; P < 0.001), GCS score ≤ 8 (OR, 6.229; P < 0.001), head or neck AIS score ≥ 4 (OR, 1.912; P = 0.003), and ISS by point increase (OR, 1.042; P < 0.001) were significant risk factors.ConclusionIn severe trauma patients, age, initial SBP, GCS score, head or neck AIS score, and ISS were associated with mortality.
This study was designed to provide a basis for building a master plan for a regional trauma system by analyzing the distribution of trauma deaths in the most populous province in Korea. Materials and Methods: We investigated the time distribution to death for trauma patients who died between January and December 2017. The time distribution to death was categorized into four groups (within a day, within a week, within a month, and over a month). Additionally, the distribution of deaths within 24 hours was further analyzed. We also reviewed the distribution of deaths according to the cause of death and mechanism of injury. Results: Of the 1546 trauma deaths, 328 cases were included in the final study population. Patients who died within a day were the most prevalent (40.9%). Of those who died within a day, the cases within an hour accounted for 40.3% of the highest proportion. The majority of trauma deaths within 4 hours were caused by traffic-related accidents (60.4%). The deaths caused by bleeding and central nervous system injuries accounted for most (70.1%) of the early deaths, whereas multi-organ dysfunction syndrome/sepsis had the highest ratio (69.7%) in the late deaths. Statistically significant differences were found in time distribution according to the mechanism of injury and cause of death (p<0.001). Conclusion: The distribution of overall timing of death was shown to follow a bimodal pattern rather than a trimodal model in Korea. Based on our findings, a suitable and modified trauma system must be developed.
Background: Trauma mortality review is the first step in assessing the quality of the trauma treatment system and provides an important basis for establishing a regional inclusive trauma system. This study aimed to obtain a reliable measure of the preventable trauma death rate in a single province in Korea. Methods: From January to December 2017, a total of 500 sample cases of trauma-related deaths from 64 hospitals in Gyeonggi Province were included. All cases were evaluated for preventability and opportunities for improvement using a multidisciplinary panel review approach. Results: Overall, 337 cases were included in the calculation for the preventable trauma death rate. The preventable trauma death rate was estimated at 17.0%. The odds ratio was 3.97 folds higher for those who arrived within "1-3 hours" than those who arrived within "1 hour." When the final treatment institution was not a regional trauma center, the odds ratio was 2.39 folds higher than that of a regional trauma center. The most significant stage of preventable trauma death was the hospital stage, during which 86.7% of the cases occurred, of which only 10.3% occurred in the regional trauma center, whereas preventable trauma death was more of a problem at emergency medical institutions. Conclusion: The preventable trauma death rate was slightly lower in this study than in previous studies, although several problems were noted during inter-hospital transfer; in the hospital stage, more problems were noted at emergency medical care facilities than at regional trauma centers. Further, several opportunities for improvements were discovered regarding bleeding control.
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