Predicting outcome after traumatic brain injury: Development and validation of a prognostic score based on admission characteristics
Predicting outcome after traumatic brain injury: Development and validation of a prognostic score based on admission characteristics
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DOI：
10.1089/neu.2005.22.1025
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发表时间：
2005-10-01
影响因子：
4.2
通讯作者：
Maas, AIR
中科院分区：
文献类型：
--
作者：
Hukkelhoven, CWPM;Steyerberg, EW;Maas, AIR
早期预测创伤性脑损伤(TBI)后的预后具有重要的意义，但尚未开发出在不同环境下被证明具有普适性的预后模型。这项研究的目的是开发和验证预后模型，这些模型使用入院时可用的信息来估计重度或中度脑外伤后6个月的结果。为此，这项研究评估了受伤后6个月的死亡率和不良结局，即在格拉斯哥预后量表(GOS)上的死亡和植物或严重残疾。前瞻性收集了来自两个多中心临床试验的2269名患者的数据，用Logistic回归分析建立了每个结果的预后模型。我们包括7个预测特征--年龄、运动评分、瞳孔反应性、低氧、低血压、计算机断层扫描分类和外伤性蛛网膜下腔出血。这些模型通过自举技术进行了内部验证。外部效度是在前瞻性收集的数据中确定的，这些数据来自欧洲(n=796)和北美(n=746)的两项相对未选定的调查。我们用受试者工作特征曲线(AUC)下的面积来评估辨别能力，即区分不同预后的患者的能力。此外，我们用Hosmer-Lemesow拟合优度检验来确定校准，即预测结果和观察结果之间的一致性。模型对发展人口的区分性较好(AUC为0.78~0.80)。外部效度更好(AUC为0.83~0.89)。校准不太令人满意，北美调查(p<；0.001)的外部效度较差。尤其是预后不良的患者，观察到的风险比预测的要高。为了便于临床应用，从回归模型中得到了积分图。使用基线特征的相对简单的预后模型可以准确地预测重度或中度颅脑损伤患者的6个月预后。较高的辨别能力表明该模型具有根据预后风险对患者进行分类的潜力。
The early prediction of outcome after traumatic brain injury (TBI) is important for several purposes, but no prognostic models have yet been developed with proven generalizability across different settings. The objective of this study was to develop and validate prognostic models that use information available at admission to estimate 6-month outcome after severe or moderate TBI. To this end, this study evaluated mortality and unfavorable outcome, that is, death, and vegetative or severe disability on the Glasgow Outcome Scale (GOS), at 6 months post-injury. Prospectively collected data on 2269 patients from two multi-center clinical trials were used to develop prognostic models for each outcome with logistic regression analysis. We included seven predictive characteristics-age, motor score, pupillary reactivity, hypoxia, hypotension, computed tomography classification, and traumatic subarachnoid hemorrhage. The models were validated internally with bootstrapping techniques. External validity was determined in prospectively collected data from two relatively unselected surveys in Europe (n = 796) and in North America (n = 746). We evaluated the discriminative ability, that is, the ability to distinguish patients with different outcomes, with the area under the receiver operating characteristic curve (AUC). Further, we determined calibration, that is, agreement between predicted and observed outcome, with the Hosmer-Lemeshow goodness-of-fit test. The models discriminated well in the development population (AUC 0.78-0.80). External validity was even better (AUC 0.83-0.89). Calibration was less satisfactory, with poor external validity in the North American survey (p < 0.001). Especially, observed risks were higher than predicted for poor prognosis patients. A score chart was derived from the regression models to facilitate clinical application. Relatively simple prognostic models using baseline characteristics can accurately predict 6-month outcome in patients with severe or moderate TBI. The high discriminative ability indicates the potential of this model for classifying patients according to prognostic risk.