• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

测量脑电图的实时药物效应。

Measuring Real-Time Medication Effects From Electroencephalography.

机构信息

Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, U.S.A.

Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, U.S.A.

出版信息

J Clin Neurophysiol. 2024 Jan 1;41(1):72-82. doi: 10.1097/WNP.0000000000000946. Epub 2022 May 17.

DOI:10.1097/WNP.0000000000000946
PMID:35583401
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9669285/
Abstract

PURPOSE

Evaluating the effects of antiseizure medication (ASM) on patients with epilepsy remains a slow and challenging process. Quantifiable noninvasive markers that are measurable in real-time and provide objective and useful information could guide clinical decision-making. We examined whether the effect of ASM on patients with epilepsy can be quantitatively measured in real-time from EEGs.

METHODS

This retrospective analysis was conducted on 67 patients in the long-term monitoring unit at Boston Children's Hospital. Two 30-second EEG segments were selected from each patient premedication and postmedication weaning for analysis. Nonlinear measures including entropy and recurrence quantitative analysis values were computed for each segment and compared before and after medication weaning.

RESULTS

Our study found that ASM effects on the brain were measurable by nonlinear recurrence quantitative analysis on EEGs. Highly significant differences ( P < 1e-11) were found in several nonlinear measures within the seizure zone in response to antiseizure medication. Moreover, the size of the medication effect correlated with a patient's seizure frequency, seizure localization, number of medications, and reported seizure frequency reduction on medication.

CONCLUSIONS

Our findings show the promise of digital biomarkers to measure medication effects and epileptogenicity.

摘要

目的

评估抗癫痫药物(ASM)对癫痫患者的影响仍然是一个缓慢而具有挑战性的过程。能够实时测量的、具有可量化的、无创性的标志物,可以提供客观有用的信息,从而指导临床决策。我们研究了从 EEG 中是否可以实时定量测量 ASM 对癫痫患者的影响。

方法

本回顾性分析在波士顿儿童医院的长期监测病房中对 67 名患者进行。在每个患者的药物预治疗和药物逐渐减停后,分别选择两个 30 秒的 EEG 片段进行分析。对每个片段计算了包括熵和递归定量分析值在内的非线性测量值,并比较了药物逐渐减停前后的变化。

结果

我们的研究发现,通过 EEG 上的非线性递归定量分析可以测量 ASM 对大脑的影响。在抗癫痫药物作用下,癫痫区域内的几个非线性测量指标存在非常显著的差异(P<1e-11)。此外,药物作用的大小与患者的癫痫发作频率、癫痫发作部位、药物种类以及药物治疗后癫痫发作频率的降低相关。

结论

我们的研究结果表明,数字生物标志物具有测量药物疗效和致痫性的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/9d9fbcb49933/jcnp-41-72-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/c626fa96e7ad/jcnp-41-72-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/7b919e27c53a/jcnp-41-72-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/75444032851e/jcnp-41-72-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/9c14bf36092c/jcnp-41-72-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/811a8488fe01/jcnp-41-72-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/23db03c7c5ed/jcnp-41-72-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/fba2132573be/jcnp-41-72-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/9d9fbcb49933/jcnp-41-72-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/c626fa96e7ad/jcnp-41-72-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/7b919e27c53a/jcnp-41-72-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/75444032851e/jcnp-41-72-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/9c14bf36092c/jcnp-41-72-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/811a8488fe01/jcnp-41-72-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/23db03c7c5ed/jcnp-41-72-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/fba2132573be/jcnp-41-72-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c6/10756694/9d9fbcb49933/jcnp-41-72-g008.jpg

相似文献

1
Measuring Real-Time Medication Effects From Electroencephalography.测量脑电图的实时药物效应。
J Clin Neurophysiol. 2024 Jan 1;41(1):72-82. doi: 10.1097/WNP.0000000000000946. Epub 2022 May 17.
2
Prognostic implications of persistent interictal epileptiform discharges on antiseizure medication withdrawal in patients with epilepsy in five-year remission.在五年缓解期的癫痫患者中,持续性发作间期癫痫样放电对抗癫痫药物停药的预后意义。
Seizure. 2022 Jan;94:100-106. doi: 10.1016/j.seizure.2021.11.009. Epub 2021 Nov 29.
3
Explainable AI for wearable seizure logging: Impact of data quality, patient age, and antiseizure medication on performance.可解释人工智能在可穿戴式癫痫记录中的应用:数据质量、患者年龄和抗癫痫药物对性能的影响。
Seizure. 2023 Aug;110:99-108. doi: 10.1016/j.seizure.2023.06.002. Epub 2023 Jun 8.
4
Effect of the revised definition of epilepsy on treatment decisions and seizure recurrence after a first epileptic seizure.修订版癫痫定义对首次癫痫发作后治疗决策和发作复发的影响。
Eur J Neurol. 2023 Jun;30(6):1557-1564. doi: 10.1111/ene.15769. Epub 2023 Mar 26.
5
Prognostic interictal electroencephalographic biomarkers and models to assess antiseizure medication efficacy for clinical practice: A scoping review.预测性发作间期脑电图生物标志物和模型评估抗癫痫药物疗效用于临床实践:范围综述。
Epilepsia. 2023 May;64(5):1125-1174. doi: 10.1111/epi.17548. Epub 2023 Mar 16.
6
Patterns of anti-seizure medication (ASM) use in pediatric patients with surgically managed epilepsy: A retrospective review of data from Boston Children's Hospital.手术治疗癫痫的儿科患者中抗癫痫药物(ASM)使用模式:来自波士顿儿童医院数据的回顾性研究。
Epilepsy Res. 2020 Feb;160:106257. doi: 10.1016/j.eplepsyres.2019.106257. Epub 2020 Jan 8.
7
Risk of seizure relapse and long-term outcomes after discontinuation of antiseizure medication in children with epilepsy.儿童癫痫患者停药后癫痫复发风险和长期结局。
Epilepsy Behav. 2022 Sep;134:108779. doi: 10.1016/j.yebeh.2022.108779. Epub 2022 Jun 25.
8
A pharmacokinetic model of antiseizure medication load to guide care in the epilepsy monitoring unit.抗癫痫药物负荷的药代动力学模型指导癫痫监测单元的护理。
Epilepsia. 2023 May;64(5):1236-1247. doi: 10.1111/epi.17558. Epub 2023 Mar 17.
9
Clinical and EEG factors associated with antiseizure medication resistance in idiopathic generalized epilepsy.特发性全身性癫痫中与抗癫痫药物耐药性相关的临床和脑电图因素。
Epilepsia. 2022 Jan;63(1):150-161. doi: 10.1111/epi.17104. Epub 2021 Oct 27.
10
Patients with psychogenic nonepileptic seizures and suspected epilepsy: An antiseizure medication reduction study.患有精神性非癫痫性发作和疑似癫痫的患者:一项抗癫痫药物减量研究。
Epilepsy Behav. 2023 Apr;141:109116. doi: 10.1016/j.yebeh.2023.109116. Epub 2023 Feb 18.

引用本文的文献

1
Entropy in Clinical Decision-Making: A Narrative Review Through the Lens of Decision Theory.临床决策中的熵:基于决策理论视角的叙述性综述
J Gen Intern Med. 2025 Sep 18. doi: 10.1007/s11606-025-09868-x.
2
Anti-seizure medication tapering correlates with daytime delta band power reduction in the cortex.抗癫痫药物逐渐减量与皮质中白天δ频段功率降低相关。
Brain Commun. 2025 Feb 25;7(1):fcaf020. doi: 10.1093/braincomms/fcaf020. eCollection 2025.