Department of Neurosurgery, Shanghai Sixth People Hospital, Shanghai Jiaotong University, Shanghai, China.
J Trauma Acute Care Surg. 2012 Jul;73(1):137-45. doi: 10.1097/TA.0b013e31824b00ac.
Early estimation of prognosis for the patient with traumatic brain injury is an important factor in making treatment decisions, resource allocation, classify patients, or communicating with family. We aimed to develop and validate practical prognostic models for mortality at 30 days and for 6 months unfavorable outcome after moderate and severe traumatic brain injury.
Retrospectively collected data from our department were used to develop prognostic models for outcome. We developed four prognostic models based on admission predictors with logistic regression analysis. The performance of models was assessed with respect to discrimination and calibration. Discriminative ability was evaluated with C statistic, equal to the area under the receiver operating characteristic curve. Calibrative ability was assessed with the Hosmer-Lemeshow test (H-L test). The internal validity of models was evaluated with the bootstrap re-sampling technique. We validated three of the models in an external series of 203 patients that collected from another research center. Discrimination and calibration were further assessed to indicate the performance of the models in external patients.
Logistic regression showed that age, pupillary reactivity, motor Glasgow Coma Score, computed tomography characters, glucose, hemoglobin, D-dimer, serum calcium, and intracranial pressure were independent prognostic factors of outcome. The models discriminated well in the development patients (C statistic 0.709-0.939). We extensively validate three of the models. Internal validation showed no overoptimism in any of the models' predictive C statistics. External validity was much better (C statistic 0.844-0.902). Calibration was also good (H-L tests, p > 0.05). Computer-based calculator that based on prognostic models was developed for clinical use.
Our validated prognostic models have good performance and are generalizable to be used to predict outcome of new patients. We recommend the use of prognostic models to complement clinical decision making.
对于创伤性脑损伤患者，早期预后评估是制定治疗决策、资源分配、患者分类或与家属沟通的重要因素。我们旨在开发和验证适用于中重度创伤性脑损伤患者 30 天死亡率和 6 个月不良预后的实用预后模型。
我们使用来自本部门的回顾性数据来开发预后模型。我们基于逻辑回归分析，使用入院预测因子开发了四个预后模型。使用 C 统计量（等于受试者工作特征曲线下的面积）评估模型的区分能力。校准能力通过 Hosmer-Lemeshow 检验（H-L 检验）进行评估。模型的内部有效性通过自举重采样技术进行评估。我们在另一个研究中心收集的 203 例外部患者系列中验证了其中三个模型。进一步评估了区分和校准，以表明模型在外部患者中的性能。
逻辑回归显示，年龄、瞳孔反应性、运动格拉斯哥昏迷评分、计算机断层扫描特征、血糖、血红蛋白、D-二聚体、血清钙和颅内压是结局的独立预后因素。这些模型在发展患者中具有良好的区分能力（C 统计量 0.709-0.939）。我们广泛验证了其中三个模型。内部验证表明，任何模型的预测 C 统计量都没有过度乐观。外部有效性要好得多（C 统计量 0.844-0.902）。校准也很好（H-L 检验，p>0.05）。为临床使用开发了基于预后模型的计算机计算器。
我们验证的预后模型具有良好的性能，可推广用于预测新患者的结局。我们建议使用预后模型来补充临床决策。
