Department of Surgery, Chandler Regional Medical Center, Chandler, Arizona, USA.
Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA.
Br J Surg. 2018 Apr;105(5):513-519. doi: 10.1002/bjs.10764. Epub 2018 Feb 21.
The Trauma Audit and Research Network (TARN) in the UK publicly reports hospital performance in the management of trauma. The TARN risk adjustment model uses a fractional polynomial transformation of the Injury Severity Score (ISS) as the measure of anatomical injury severity. The Trauma Mortality Prediction Model (TMPM) is an alternative to ISS; this study compared the anatomical injury components of the TARN model with the TMPM.
Data from the National Trauma Data Bank for 2011-2015 were analysed. Probability of death was estimated for the TARN fractional polynomial transformation of ISS and compared with the TMPM. The coefficients for each model were estimated using 80 per cent of the data set, selected randomly. The remaining 20 per cent of the data were used for model validation. TMPM and TARN were compared using calibration curves, measures of discrimination (area under receiver operating characteristic curves; AUROC), proximity to the true model (Akaike information criterion; AIC) and goodness of model fit (Hosmer-Lemeshow test).
Some 438 058 patient records were analysed. TMPM demonstrated preferable AUROC (0·882 for TMPM versus 0·845 for TARN), AIC (18 204 versus 21 163) and better fit to the data (32·4 versus 153·0) compared with TARN.
TMPM had greater discrimination, proximity to the true model and goodness-of-fit than the anatomical injury component of TARN. TMPM should be considered for the injury severity measure for the comparative assessment of trauma centres.
英国的创伤审核和研究网络(TARN)公开报告医院在创伤管理方面的绩效。TARN 风险调整模型使用损伤严重度评分(ISS)的分数多项式变换作为解剖损伤严重程度的衡量标准。创伤死亡率预测模型(TMPM)是 ISS 的替代方法;本研究比较了 TARN 模型的解剖损伤成分与 TMPM。
对 2011-2015 年国家创伤数据库的数据进行了分析。使用 TARN 的 ISS 分数多项式变换估计了死亡概率,并与 TMPM 进行了比较。使用 80%的数据随机选择,估计了每个模型的系数。其余 20%的数据用于模型验证。使用校准曲线、判别力(接受者操作特征曲线下的面积;AUROC)、接近真实模型(Akaike 信息准则;AIC)和模型拟合优度(Hosmer-Lemeshow 检验)比较了 TMPM 和 TARN。
分析了 438058 例患者的记录。与 TARN 相比,TMPM 显示出更好的 AUROC(TMPM 为 0.882,TARN 为 0.845)、AIC(18204 比 21163)和更好的数据拟合(32.4 比 153.0)。
与 TARN 的解剖损伤成分相比,TMPM 的判别力、接近真实模型和拟合优度更高。TMPM 应被视为比较创伤中心的损伤严重度测量标准。