Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands.
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
J Neurotrauma. 2023 Aug;40(15-16):1651-1670. doi: 10.1089/neu.2022.0320. Epub 2023 May 24.
After mild traumatic brain injury (mTBI), a substantial proportion of individuals do not fully recover on the Glasgow Outcome Scale Extended (GOSE) or experience persistent post-concussion symptoms (PPCS). We aimed to develop prognostic models for the GOSE and PPCS at 6 months after mTBI and to assess the prognostic value of different categories of predictors (clinical variables; questionnaires; computed tomography [CT]; blood biomarkers). From the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we included participants aged 16 or older with Glasgow Coma Score (GCS) 13-15. We used ordinal logistic regression to model the relationship between predictors and the GOSE, and linear regression to model the relationship between predictors and the Rivermead Post-concussion Symptoms Questionnaire (RPQ) total score. First, we studied a pre-specified Core model. Next, we extended the Core model with other clinical and sociodemographic variables available at presentation (Clinical model). The Clinical model was then extended with variables assessed before discharge from hospital: early post-concussion symptoms, CT variables, biomarkers, or all three categories (extended models). In a subset of patients mostly discharged home from the emergency department, the Clinical model was extended with 2-3-week post-concussion and mental health symptoms. Predictors were selected based on Akaike's Information Criterion. Performance of ordinal models was expressed as a concordance index (C) and performance of linear models as proportion of variance explained (R2). Bootstrap validation was used to correct for optimism. We included 2376 mTBI patients with 6-month GOSE and 1605 patients with 6-month RPQ. The Core and Clinical models for GOSE showed moderate discrimination (C = 0.68 95% confidence interval 0.68 to 0.70 and C = 0.70[0.69 to 0.71], respectively) and injury severity was the strongest predictor. The extended models had better discriminative ability (C = 0.71[0.69 to 0.72] with early symptoms; 0.71[0.70 to 0.72] with CT variables or with blood biomarkers; 0.72[0.71 to 0.73] with all three categories). The performance of models for RPQ was modest (R2 = 4% Core; R2 = 9% Clinical), and extensions with early symptoms increased the R2 to 12%. The 2-3-week models had better performance for both outcomes in the subset of participants with these symptoms measured (C = 0.74 [0.71 to 0.78] vs. C = 0.63[0.61 to 0.67] for GOSE; R2 = 37% vs. 6% for RPQ). In conclusion, the models based on variables available before discharge have moderate performance for the prediction of GOSE and poor performance for the prediction of PPCS. Symptoms assessed at 2-3 weeks are required for better predictive ability of both outcomes. The performance of the proposed models should be examined in independent cohorts.
颅脑外伤后轻度创伤性脑损伤(mTBI)后,相当一部分患者在格拉斯哥结局量表扩展版(GOSE)上未完全恢复或仍存在持续性脑震荡后症状(PPCS)。我们旨在为 mTBI 后 6 个月的 GOSE 和 PPCS 建立预后模型,并评估不同类别预测因素(临床变量;问卷;计算机断层扫描 [CT];血液生物标志物)的预后价值。来自协作性欧洲神经创伤有效性研究颅脑外伤(CENTER-TBI)研究,我们纳入了年龄在 16 岁及以上且格拉斯哥昏迷评分(GCS)为 13-15 的患者。我们使用有序逻辑回归来模拟预测因素与 GOSE 之间的关系,以及线性回归来模拟预测因素与 Rivermead 脑震荡后症状问卷(RPQ)总分之间的关系。首先,我们研究了一个预先指定的核心模型。接下来,我们在出现时将核心模型扩展到其他临床和社会人口学变量(临床模型)。然后,将在医院出院前评估的变量(早期脑震荡症状、CT 变量、生物标志物或所有三个类别)扩展到临床模型中(扩展模型)。在从急诊室主要出院回家的患者亚组中,将 2-3 周的脑震荡后和心理健康症状扩展到临床模型中。预测因子是根据赤池信息量准则选择的。有序模型的性能用一致性指数(C)表示,线性模型的性能用解释方差的比例(R2)表示。使用自举验证来纠正乐观偏差。我们纳入了 2376 例 mTBI 患者,他们在 6 个月时进行了 GOSE 评估,1605 例患者在 6 个月时进行了 RPQ 评估。GOSE 的核心和临床模型显示出中等的区分能力(C=0.68[0.68 至 0.70]和 C=0.70[0.69 至 0.71],分别),损伤严重程度是最强的预测因素。扩展模型具有更好的区分能力(C=0.71[0.69 至 0.72]与早期症状;C=0.71[0.70 至 0.72]与 CT 变量或血液生物标志物;C=0.72[0.71 至 0.73]与所有三个类别)。RPQ 模型的性能适中(R2=4%核心;R2=9%临床),早期症状的扩展将 R2 提高到 12%。在有这些症状的参与者亚组中,2-3 周的模型对这两种结果都有更好的表现(C=0.74[0.71 至 0.78]与 C=0.63[0.61 至 0.67]用于 GOSE;R2=37%与 6%用于 RPQ)。总之,基于出院前可用变量的模型对 GOSE 的预测具有中等性能,对 PPCS 的预测性能较差。需要在 2-3 周时评估症状,以提高两种结果的预测能力。建议的模型的性能应在独立队列中进行检查。