A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy
文献类型：期刊论文
| 作者 | Cheng, Tung-yang7; Hu, Yingbing6,7; Qin, Xiaoya6,7; Ma, Jiayi5; Zha, Daqi7; Xie, Han5; Ji, Taoyun1,5; Liu, Qingzhu1; Wang, Zhiyan3,4; Hao, Hongwei7 |
| 刊名 | CNS NEUROSCIENCE & THERAPEUTICS
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| 出版日期 | 2024-07-01 |
| 卷号 | 30期号:7页码:12 |
| 关键词 | drug-resistant epilepsy functional connectivity Hilbert-Huang spectral entropy support vector machine Vagus nerve stimulation |
| ISSN号 | 1755-5930 |
| DOI | 10.1111/cns.14751 |
| 通讯作者 | Wang, Zhiyan(wzyann@126.com) ; Hao, Hongwei(haohw@tsinghua.edu.cn) ; Wu, Ye(dryewu@263.net) |
| 英文摘要 | AimsTo predict the vagus nerve stimulation (VNS) efficacy for pediatric drug-resistant epilepsy (DRE) patients, we aim to identify preimplantation biomarkers through clinical features and electroencephalogram (EEG) signals and thus establish a predictive model from a multi-modal feature set with high prediction accuracy.MethodsSixty-five pediatric DRE patients implanted with VNS were included and followed up. We explored the topological network and entropy features of preimplantation EEG signals to identify the biomarkers for VNS efficacy. A Support Vector Machine (SVM) integrated these biomarkers to distinguish the efficacy groups.ResultsThe proportion of VNS responders was 58.5% (38/65) at the last follow-up. In the analysis of parieto-occipital alpha band activity, higher synchronization level and nodal efficiency were found in responders. The central-frontal theta band activity showed significantly lower entropy in responders. The prediction model reached an accuracy of 81.5%, a precision of 80.1%, and an AUC (area under the receiver operating characteristic curve) of 0.838.ConclusionOur results revealed that, compared to nonresponders, VNS responders had a more efficient alpha band brain network, especially in the parieto-occipital region, and less spectral complexity of theta brain activities in the central-frontal region. We established a predictive model integrating both preimplantation clinical and EEG features and exhibited great potential for discriminating the VNS responders. This study contributed to the understanding of the VNS mechanism and improved the performance of the current predictive model. The long-term efficacy of VNS was assessed among 65 pediatric patients. Presurgical EEG analysis shows that VNS responders exhibit higher nodal efficiency in parietal-occipital EEG alpha activity and lower entropy in central-frontal EEG theta activity. The SVM model with clinical and EEG features for VNS efficacy shows high accuracy.image |
| 收录类别 | SCI |
| WOS关键词 | REFRACTORY EPILEPSY ; EEG ; VNS ; CHILDREN ; THERAPY ; DESYNCHRONIZATION ; NETWORKS ; SUCCESS ; ALPHA ; MEG |
| 资助项目 | National Natural Science Foundation of China[82101549] ; National Key Research and Development Program of China[2021YFC2401205] ; Shenzhen International Cooperation Research Project[GJHZ20180930110402104] |
| WOS研究方向 | Neurosciences & Neurology ; Pharmacology & Pharmacy |
| 语种 | 英语 |
| WOS记录号 | WOS:001268749700001 |
| 出版者 | WILEY |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program of China ; Shenzhen International Cooperation Research Project |
| 源URL | [http://ir.psych.ac.cn/handle/311026/48486]  |
| 专题 | 心理研究所_中国科学院心理健康重点实验室 |
| 通讯作者 | Wang, Zhiyan; Hao, Hongwei; Wu, Ye |
| 作者单位 | 1.Peking Univ First Hosp, Pediat Epilepsy Ctr, Beijing, Peoples R China 2.Tsinghua Univ, IDG McGovern Inst Brain Res, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Psychol, CAS Key Lab Mental Hlth, Beijing, Peoples R China 5.Peking Univ First Hosp, Dept Pediat, Beijing, Peoples R China 6.Tsinghua Univ, Tsinghua Berkeley Shenzhen Inst, Shenzhen, Peoples R China 7.Tsinghua Univ, Sch Aerosp Engn, Natl Engn Res Ctr Neuromodulat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cheng, Tung-yang,Hu, Yingbing,Qin, Xiaoya,et al. A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy[J]. CNS NEUROSCIENCE & THERAPEUTICS,2024,30(7):12. |
| APA | Cheng, Tung-yang.,Hu, Yingbing.,Qin, Xiaoya.,Ma, Jiayi.,Zha, Daqi.,...&Li, Luming.(2024).A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy.CNS NEUROSCIENCE & THERAPEUTICS,30(7),12. |
| MLA | Cheng, Tung-yang,et al."A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy".CNS NEUROSCIENCE & THERAPEUTICS 30.7(2024):12. |
入库方式： OAI收割
来源：心理研究所
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