|
|
|
| Predictive Value of Seizure Duration, Cognitive Impairment and Electroencephalogram Grading for Prognosis in Patients with NCSE |
| LI Haijing, DING Ying, DU Xiangjing |
| Department of Neuroelectrophysiology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou Henan 450000 |
|
|
|
|
Abstract 【Objective】 To explore the predictive value of seizure duration, cognitive impairment and electroencephalogram (EGG) grading for the prognosis of patients with non-convulsive status epilepticus (NCSE). 【Methods】 Clinical data of 100 patients with NCSE were collected. A multidimensional prognostic evaluation system was established using the modified Rankin Scale (mRS) combined with the Mini-Mental State Examination (MMSE). Patients were divided into a poor prognosis group (n=37) and a good prognosis group (n=63). Clinical characteristics and EEG features of the two groups were compared. Univariate analysis was performed to screen factors related to prognosis, and multivariate Logistic regression analysis was used to identify independent risk factors affecting prognosis. The predictive performance of the regression model for patient prognosis was evaluated using the receiver operating characteristic (ROC) curve. 【Results】 The proportions of disturbance of consciousness, seizure duration ≥1 h, and EEG grades 3-6 in the poor prognosis group were significantly higher than those in the good prognosis group (P<0.05), while the proportion of generalized seizures was lower than that in the good prognosis group (P<0.05). Multivariate Logistic regression analysis showed that disturbance of consciousness, seizure duration, and EEG grading were independent risk factors for poor prognosis in NCSE patients (P<0.05), whereas generalized seizures served as a protective factor (P<0.05). The area under the curve (AUC) of the regression model was 0.929, with a sensitivity of 82.4% and a specificity of 90.4%. 【Conclusion】 Disturbance of consciousness, seizure duration, EEG grading, and generalized seizures are closely associated with the prognosis of NCSE patients. The regression model shows high predictive efficiency and is of significant value for guiding clinical treatment.
|
|
Received: 11 September 2025
|
|
|
|
|
|
[1] 邓会芳,孙婧,王博,等. 神经重症患者非惊厥性癫痫持续状态的早期预防及分步治疗研究进展[J].中国现代医学杂志,2023,33(22):43-47.
[2] LONG B, KOYFMAN A. Nonconvulsive status epilepticus: a review for emergency clinicians[J].J Emerg Med,2023, 65(4): e259-e271.
[3] 管巧,刘刚,桑田,等. 儿童重症监护病房284例脑电图监测儿童癫痫发作的危险因素及其与预后的相关性[J].中华实用儿科临床杂志,2023,38(9):702-706.
[4] 陈洪铧,鞠玲莉,季燕燕,等. 基于总脑电图评分的发作间期脑电图分析对癫痫患者认知障碍早期评估的意义[J].中华神经科杂志,2025,58(1):36-45.
[5] LEITINGER M, BENICZKY S, ROHRACHER A, et al. Salzburg consensus criteria for non-convulsive status epilepticus:approach to clinical application[J].Epilepsy Behav,2015, 49(1): 158-163.
[6] FOLSTEIN M F, FOLSTEIN S E, MCHUGH P R. "Mini-mental state": a practical method for grading the cognitive state of patients for the clinician[J].J Psychiatr Res,1975, 12(3): 189-198.
[7] YOUNG G B. The EEG in coma[J].J Clin Neurophysiol,2000, 17(5): 473-485.
[8] MERLI E, ROMOLI M, GALLUZZO S, et al. Pragmatic computerised perfusion diagnostics for non-convulsive status epilepticus: a prospective observational study[J].J Neurol Neurosurg Psychiatry,2024, 95(5): 471-476.
[9] 金磊,支迪暄,杨彦枫,等. 立体定向脑电图引导下3D交叉射频热凝毁损术治疗药物难治性内侧颞叶癫痫伴海马硬化的有效性及安全性[J].中华医学杂志,2025,105(11):827-833.
[10] 杨锐,陈晓荣,闵朋,等. 氢质子磁共振波谱成像结合视频脑电图诊断癫痫的价值[J].中国实用神经疾病杂志,2024,27(6):691-695.
[11] 魏翔,鲁广函,刘敬轩,等. 脑电峰频率在慢性意识障碍中评估的应用现状及进展[J].临床神经外科杂志,2025,22(3):340-343.
[12] KOZAK R, GURURANGAN K, DORRIZ P J, et al. Point-of-care electroencephalography enables rapid evaluation and management of non-convulsive seizures and status epilepticus in the emergency department[J]. J Am Coll Emerg Physicians Open,2023, 4(4): e13004.
[13] 陈明武,郑诗豪,杨波,等. CTP灌注参数联合脑电图对aSAH继发癫痫及预后的价值分析[J].中国医学物理学杂志,2023,40(2):182-185.
[14] 姜卉,姜兵,张伟,等. 局灶性皮层发育不良相关难治性癫痫的手术预后影响因素分析[J].中国现代手术学杂志,2023,27(2):139-144.
[15] 王艺颖,王静. 儿童非惊厥性癫痫持续状态临床特征、脑电图特点及其对脑功能预后的影响[J].中国优生与遗传杂志,2022,30(7):1182-1186. |
|
|
|
2026, Vol. 43 
