Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
State Key Laboratory of Cancer Biology, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, China.
CNS Neurosci Ther. 2023 Dec;29(12):3935-3942. doi: 10.1111/cns.14313. Epub 2023 Jun 19.
The prediction of outcomes in convulsive status epilepticus (CSE) remains a constant challenge. The Encephalitis-Nonconvulsive Status Epilepticus-Diazepam Resistance-Image Abnormalities-Tracheal Intubation (END-IT) score was a useful tool for predicting the functional outcomes of CSE patients, excluding cerebral hypoxia patients. With further understanding of CSE, and in view of the deficiencies of END-IT itself, we consider it necessary to modify the prediction tool.
The prediction model was designed from a cohort of CSE patients from Xijing Hospital (China), between 2008 and 2020. The enrolled subjects were randomly divided into training cohort and validation cohort as a ratio of 2:1. The logistic regression analysis was performed to identify the predictors and construct the nomogram. The performance of the nomogram was assessed by calculating the concordance index, and creating calibration plots to check the consistency between the predicted probabilities of poor prognosis and the actual outcomes of CSE.
The training cohort included 131 patients and validation cohort included 66 patients. Variables included in the nomogram were age, etiology of CSE, non-convulsive SE, mechanical ventilation, abnormal albumin level at CSE onset. The concordance index of the nomogram in the training and validation cohorts was 0.853 (95% CI, 0.787-0.920) and 0.806 (95% CI, 0.683-0.923), respectively. The calibration plots showed an adequate consistency between the reported and predicted unfavorable outcomes of patients with CSE at 3 months after discharge.
A nomogram for predicting the individualized risks of poor functional outcomes in CSE was constructed and validated, which has been an important modification of END-IT score.
癫痫持续状态(CSE)的结局预测仍然是一个持续存在的挑战。脑炎-非惊厥性癫痫持续状态-地西泮耐药-影像异常-气管插管(END-IT)评分是一种预测 CSE 患者结局的有用工具,排除了脑缺氧患者。随着对 CSE 的进一步了解,并且鉴于 END-IT 本身的不足,我们认为有必要对预测工具进行修改。
该预测模型来自于 2008 年至 2020 年在中国西京医院的一组 CSE 患者。入组患者随机分为训练队列和验证队列,比例为 2:1。采用逻辑回归分析识别预测因子并构建列线图。通过计算一致性指数评估列线图的性能,并绘制校准图以检查不良预后预测概率与 CSE 实际结局之间的一致性。
训练队列纳入了 131 例患者,验证队列纳入了 66 例患者。列线图纳入的变量包括年龄、CSE 的病因、非惊厥性 SE、机械通气、CSE 发作时白蛋白水平异常。列线图在训练队列和验证队列中的一致性指数分别为 0.853(95%CI,0.787-0.920)和 0.806(95%CI,0.683-0.923)。校准图显示,在出院后 3 个月,患者的报告结局与预测的不良结局之间具有较好的一致性。
构建并验证了预测 CSE 患者不良功能结局个体化风险的列线图,这是 END-IT 评分的重要改进。