Skaga N O, Eken T, Søvik S
Division of Emergencies and Critical Care, Department of Anaesthesiology, Oslo University Hospital Ullevål, Oslo, Norway.
Division of Emergencies and Critical Care, Oslo University Hospital Trauma Registry, Oslo University Hospital Ullevål, Oslo, Norway.
Acta Anaesthesiol Scand. 2018 Feb;62(2):253-266. doi: 10.1111/aas.13029. Epub 2017 Nov 8.
Anatomic injury, physiological derangement, age, injury mechanism and pre-injury comorbidity are well-founded predictors of trauma outcome. Statistical prediction models may have poorer discrimination, calibration and accuracy when applied in new locations. We aimed to compare the TRISS, TARN and NORMIT survival prediction models in a Norwegian trauma population.
Consecutive patients admitted to Oslo University Hospital Ullevål within 24 h after injury, with Injury Severity Score ≥ 10, proximal penetrating injuries, or received by trauma team, were studied. Original NORMIT coefficients were updated in a derivation dataset (NORMIT 2; n = 5923; 2005-2009). TRISS, TARN and NORMIT prediction models were evaluated in the validation dataset (n = 6348; 2010-2013) using two different AIS editions for injury coding. Exclusion due to missing data was 0.26%. Outcome was 30-day mortality. Validation included AUROC, scaled Brier statistics, and calibration plots.
The NORMIT models had significantly better discrimination, calibration, and overall fit than the TRISS 09, TARN 09 and TARN 12 models. The updated NORMIT 2 had higher numerical values of AUROC and scaled Brier than the original NORMIT, but with overlapping 95%CI. Overlapping 95%CI for AUROCs and Discrimination slopes indicated that the TARN and TRISS models performed similarly. Calibration plots showed tight and consistent predictions over all Ps strata for NORMIT 2 run on AIS'98 coded data, and only little deterioration when AIS'08 data was substituted.
In a Norwegian trauma population, the updated Norwegian survival prediction model in trauma (NORMIT 2) performed better than well-established British and US alternatives. External validation of these three models in other Nordic populations is warranted.
解剖损伤、生理紊乱、年龄、损伤机制和伤前合并症是创伤结局的可靠预测因素。统计预测模型应用于新地点时，其区分度、校准度和准确性可能较差。我们旨在比较挪威创伤人群中的TRISS、TARN和NORMIT生存预测模型。
对伤后24小时内入住奥斯陆大学医院乌勒瓦尔分院、损伤严重程度评分≥10分、近端穿透伤或由创伤团队接诊的连续患者进行研究。在一个推导数据集（NORMIT 2；n = 5923；2005 - 2009年）中更新了原始的NORMIT系数。使用两种不同的AIS版本进行损伤编码，在验证数据集（n = 6348；2010 - 2013年）中对TRISS、TARN和NORMIT预测模型进行评估。因数据缺失导致的排除率为0.26%。结局指标为30天死亡率。验证包括受试者工作特征曲线下面积（AUROC）、标准化Brier统计量和校准图。
NORMIT模型在区分度、校准度和整体拟合方面明显优于TRISS 09、TARN 09和TARN 12模型。更新后的NORMIT 2的AUROC和标准化Brier的数值高于原始的NORMIT，但95%置信区间重叠。AUROC和区分斜率的95%置信区间重叠表明TARN和TRISS模型表现相似。校准图显示，对于使用AIS'98编码数据运行的NORMIT 2，在所有概率分层上预测紧密且一致，用AIS'08数据替代时仅略有恶化。
在挪威创伤人群中，更新后的挪威创伤生存预测模型（NORMIT 2）比成熟的英国和美国模型表现更好。有必要在其他北欧人群中对这三种模型进行外部验证。
