Ou Sijie, Sun Lanfeng, Lu Yuling, Qian Kai, Chen Suyi, Zhang Lin, Wu Yuan
Department of Neurology, Guangxi Medical University First Affiliated Hospital, Nanning, China.
J Craniofac Surg. 2024 Aug 8;36(5):1827-34. doi: 10.1097/SCS.0000000000010300.
Posttraumatic epilepsy (PTE) is considered to be one of the most severe and enduring outcomes that can arise from traumatic brain injury (TBI). The authors' study aims to create and authenticate a prognostic model for forecasting the PTE occurrence after TBI. The clinical prognostic model was developed in 475 people who had a TBI history in Nanning using a multivariate logistic regression model. The score in the authors' prognostic model participants was subjected to external validation from other cities in Guangxi and assessed its performance with the area under the receiver operating characteristic curve (area under the curve), calibration plots, and decision curve analysis. Six variables were selected to establish the nomogram for PTE, including time, Glasgow Coma Scale, location, cranial imaging (midline shift), intracranial infection, and titanium mesh cranioplasty. The area under the curve was found to be 0.860 in the training cohort and 0.735 in the validation cohort, revealing that the nomogram exhibited a satisfactory level of discriminative ability. The calibration plots exhibited a substantial degree of concordance between the prognostic predictions generated by the nomogram and the observed outcomes in both the training and validation groups. In addition, the decision curve analysis demonstrated the clinical utility of the nomogram. The cutoff value for the training cohort was determined to be 0.381, whereas for the validation cohort, it was 0.380. This suggests that patients with a probability >0.381 should be given special consideration. A prognostic nomogram was formulated and verified to aid health care clinicians in assessing the prognosis of patients with PTE.
创伤后癫痫（PTE）被认为是创伤性脑损伤（TBI）可能产生的最严重且持久的后果之一。作者的研究旨在创建并验证一个用于预测TBI后PTE发生情况的预后模型。使用多变量逻辑回归模型，在南宁475名有TBI病史的人群中开发了临床预后模型。作者预后模型参与者的得分在广西其他城市进行了外部验证，并通过受试者操作特征曲线下面积（曲线下面积）、校准图和决策曲线分析评估其性能。选择六个变量来建立PTE列线图，包括时间、格拉斯哥昏迷量表、损伤部位、头颅影像学检查（中线移位）、颅内感染和钛网颅骨成形术。训练队列的曲线下面积为0.860，验证队列的曲线下面积为0.735，表明列线图具有令人满意的鉴别能力。校准图显示，列线图生成的预后预测与训练组和验证组的观察结果之间具有高度一致性。此外，决策曲线分析证明了列线图的临床实用性。训练队列的截断值确定为0.381，而验证队列的截断值为0.380。这表明概率>0.381的患者应给予特别关注。制定并验证了一个预后列线图，以帮助医疗保健临床医生评估PTE患者的预后。
