基于神经因子及定量脑电图指标构建脑卒中后癫痫认知障碍的预测模型

doi:10.3969/j.issn.1671-7171.2025.12.017

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Abstract 【Objective】 To investigate the development of a predictive model for post-stroke epilepsy cognitive impairment (PSCI) in elderly patients, based on neurotrophic factors and quantitative electroencephalography (QEEG) indicators.【Methods】 A total of 106 elderly patients with post-stroke epilepsy were enrolled. According to the Montreal Cognitive Assessment-Basic (MoCA-B) scores, patients were divided into the PSCI (post-stroke epilepsy cognitive impairment) group (79 cases) and the PSCN (post-stroke epilepsy cognitive normal) group (27 cases). Serum levels of brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF), and QEEG indicators [α wave, β wave, θ wave, δ wave ratio,θ/α(TAR), and (θ+δ)/(α+β)(DTABR) ratio] were compared between the two groups. Binary logistic regression analysis was used to identify influencing factors of PSCI in elderly patients with post-stroke epilepsy. A nomogram prediction model was then constructed, and its predictive performance and accuracy were evaluated.【Results】 The PSCI group showed lower BDNF and α-wave ratio, and higher NGF, θ wave ratio, TAR, and DTABR compared with the PSCN group (all P<0.05). There were no statistically significant differences in β wave or δ wave between the two groups (P>0.05). Logistic regression analysis indicated that BDNF and α wave ratio were protective factors for PSCI, while NGF, θ wave, TAR, and DTABR were risk factors. Model validation demonstrated a concordance index of 0.932, with the calibration curve closely aligned with the ideal curve, indicating good accuracy and consistency.【Conclusion】 A predictive model based on neurotrophic factors and QEEG indicators can effectively assess the risk of cognitive impairment in elderly patients with post-stroke epilepsy, providing a valuable reference for clinical practice.

Key words： Stroke Epilepsy Cognition Disorders Nerve Growth Factors Electroencephalography

Received: 24 June 2025

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R743

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	LIU Xiao
	LU Zhe

Cite this article:

LIU Xiao,LU Zhe. Construction of a Predictive Model for Post-Stroke Epilepsy Cognitive Impairment Based on Neurotrophic Factors and Quantitative Electroencephalography Indicators[J]. JOURNAL OF CLINICAL RESEARCH, 2025, 42(12): 2075-2078.

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http://journal07.magtech.org.cn/yxlcyj/EN/10.3969/j.issn.1671-7171.2025.12.017 OR http://journal07.magtech.org.cn/yxlcyj/EN/Y2025/V42/I12/2075

[1] 吕英雷,杜录,高星,等. 定量脑电图检查指标与老年首次脑卒中后认知功能的相关性[J].中国神经免疫学和神经病学杂志,2022,29(2):165-168.
[2] 朱好春,葛晗明,赵航,等. 艾司西酞普兰联合拉莫三嗪对脑卒中后癫痫共病抑郁患者心理和神经功能的影响[J].国际精神病学杂志,2020,47(6):1175-1177.
[3] 贾莉子,李晓燕,杜宁. 缺血性脑卒中病人定量脑电图参数与梗死面积、NIHSS评分的相关性[J].中西医结合心脑血管病杂志,2023,21(1):161-164.
[4] 程启慧,余丹,杨国帅,等. 血清碱性磷酸酶和脂蛋白相关磷脂酶A2对缺血性脑卒中后认知功能障碍的预测价值[J].中国慢性病预防与控制,2020,28(12):917-921.
[5] 中华医学会神经病学分会,中华医学会神经病学分会脑血管病学组. 中国急性缺血性脑卒中诊治指南2018[J].中华神经科杂志,2018,51(9):666-682.
[6] HOLTKAMP M, BEGHI E, BENNINGER F,et al. European Stroke Organisation guidelines for the management of post-stroke seizures and epilepsy[J].Eur Stroke J,2017,2(2):103-115.
[7] 张静,赵建华,刘娜,等. 脑卒中后癫痫发作的预测因素及预后[J].中华行为医学与脑科学杂志,2022,31(5):414-419.
[8] 张婧,张魁,巩利,等. 血清脑源性神经营养因子预测急性缺血性卒中患者卒中后认知损害[J].国际脑血管病杂志,2022,30(2):99-103.
[9] 喻蕾,郝新斌,葛秋颖. 急性脑梗死患者CXCL12、PTX-3、FⅦa/FⅦAg比值与定量脑电图指标的相关性[J].检验医学,2022,37(2):194-195.
[10] NIKOLAC P M, BOROVECKI F, FILIPCIC I, et al. Relationship between brain-derived neurotrophic factor and cognitive decline in patients with mild cognitive impairment and dementia[J].Biomolecules,2023,13(3):570.
[11] 霍彦,姚丽珍,王刚. 血清脑源性神经营养因子、B细胞活化因子、胶质酸性纤维蛋白与癫痫患者病情及认知功能的相关性分析[J].实用医院临床杂志,2022,19(6):154-157.
[12] ZHANG E, LIAO P. Brain-derived neurotrophic factor and post-stroke depression[J].J Neurosci Res,2020,98(3):537-548.
[13] FAROKHI-SISAKHT F, FARHOUDI M, SADIGH-ETEGHAD S,et al. Cognitive rehabilitation improves ischemic stroke-induced cognitive impairment: role of growth factors[J].J Stroke Cerebrovasc Dis,2019,28(10):104299.
[14] SAES M, MESKERS C G M, DAFFERTSHOFER A,et al. Are early measured resting-state EEG parameters predictive for upper limb motor impairment six months poststroke?[J].Clin Neurophysiol,2021,132(1):56-62.
[15] DOERRFUSS J I, KILIC T, AHMADI M,et al. Quantitative and qualitative EEG as a prediction tool for outcome and complications in acute stroke patients[J].Clin EEG Neurosci,2020,51(2):121-129.
[16] ABE S, TANAKA T, FUKUMA K,et al. Interictal epileptiform discharges as a predictive biomarker for recurrence of poststroke epilepsy[J].Brain Commun,2022,4(6):fcac312.