So Jungsub, Jung Kyoungwon, Kwon Junsik, Kang Byung Hee, Lee Yo Han, Lee Eun Hae, Park Chan Ik, Cho Jayun, Park Hoonsung, Song Seoyoung, Yoo Jayoung, Heo Inhae
Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea.
Gyeonggi South Regional Trauma Center, Ajou University Hospital, Suwon, Korea.
J Korean Med Sci. 2025 Jun 30;40(25):e122. doi: 10.3346/jkms.2025.40.e122.
Since the Trauma and Injury Severity Score (TRISS) was first developed in 1987, it has been widely used to predict trauma outcomes. However, numerous attempts have been made to adjust coefficients or develop new prediction models, as TRISS may not align with the local conditions. This study aimed to develop a Korean-TRISS (K-TRISS) model suitable for the Korean population.
We analyzed data from adult patients with blunt trauma in the Korea Trauma Data Bank (KTDB) from January 2017 to December 2021. A new set of TRISS coefficients (K-TRISS-1) was derived from the study data using a logistic regression method. We compared the predictive ability of the K-TRISS-1 with the previous Major Trauma Outcome Study (MTOS) in 1987 and the National Trauma Data Bank (NTDB) model in 2009. The predictive power of the models was evaluated with the area under receiver operating characteristic (AUROC) curves, and the validity was evaluated with the C-statistic and bootstrap verification methods. Additionally, we enhanced the model construction (K-TRISS-2) by converting the age variable from a categorical format to a continuous one.
Overall, 128,534 cases were included in the statistical analysis. The comparison of AUROC values indicated that K-TRISS-1 (0.9232) outperformed MTOS (0.9210) and NTDB (0.9190), with their 95% confidence intervals showing some tendency (0.9196-0.9267, 0.9200-0.9230, and 0.9180-0.9210, respectively). However, K-TRISS-2 (0.9336, 0.9305-0.9367) had a significantly higher AUROC value compared to those of the others and showed excellent predictive power in the C-statistic and bootstrap tests.
This study proposes the K-TRISS model, derived from the KTDB, which does not significantly differ from the previous models in terms of predictive power. Furthermore, we were able to construct a model demonstrating improved predictive power when converting age to a continuous variable.
自1987年首次开发创伤和损伤严重程度评分（TRISS）以来，它已被广泛用于预测创伤结局。然而，由于TRISS可能与当地情况不符，人们进行了许多尝试来调整系数或开发新的预测模型。本研究旨在开发一种适用于韩国人群的韩国TRISS（K-TRISS）模型。
我们分析了韩国创伤数据库（KTDB）中2017年1月至2021年12月成年钝性创伤患者的数据。使用逻辑回归方法从研究数据中得出一组新的TRISS系数（K-TRISS-1）。我们将K-TRISS-1的预测能力与1987年以前的重大创伤结局研究（MTOS）和2009年的国家创伤数据库（NTDB）模型进行了比较。用受试者操作特征曲线下面积（AUROC）评估模型的预测能力，用C统计量和自助验证方法评估模型的有效性。此外，我们通过将年龄变量从分类格式转换为连续格式来加强模型构建（K-TRISS-2）。
总体而言，128534例病例纳入统计分析。AUROC值比较表明，K-TRISS-1（0.9232）优于MTOS（0.9210）和NTDB（0.9190），其95%置信区间显示出一定趋势（分别为0.9196 - 0.9267、0.9200 - 0.9230和0.9180 - 0.9210）。然而，K-TRISS-2（0.9336，0.9305 - 0.9367）的AUROC值显著高于其他模型，并且在C统计量和自助检验中显示出优异的预测能力。
本研究提出了源自KTDB的K-TRISS模型，其在预测能力方面与先前模型无显著差异。此外，当将年龄转换为连续变量时，我们能够构建一个预测能力有所提高的模型。
