脑电图与体感诱发电位在意识障碍患者诊断及预后评估中的应用
Application of Electroencephalography and Somatosensory Evoked Potentials in the Diagnosis and Prognostic Evaluation of Patients with Disorders of Consciousness
DOI: 10.12677/acm.2025.1551372, PDF,   
作者: 唐云乐, 肖 农*:重庆医科大学附属儿童医院康复科,国家儿童健康与疾病临床医学研究中心,儿童发育疾病研究教育部重点实验室,儿科学重庆市重点实验室,重庆
关键词: 意识障碍脑电图体感诱发电位诊断预后Disorders of Consciousness (DoC) Electroencephalography (EEG) Somatosensory Evoked Potentials (SSEPs) Diagnosis Prognosis
摘要: 意识障碍(Disorders of Consciousness, DoC)是指严重脑损伤导致的觉醒与觉知功能受损状态,包括昏迷、植物状态(VS/UWS)和微小意识状态(MCS)。意识障碍一直是神经科学领域的重要研究课题,其诊断与预后评估对临床决策、医疗资源分配及患者家庭支持具有深远意义,这也是临床实践中的难点。传统的行为学量表评估方法存在主观性强、误诊率高的问题,难以满足现代医学对客观、精准诊断的需求。近年来,脑电图(Electroencephalography, EEG)和体感诱发电位(Somatosensory Evoked Potentials, SSEPs)等神经电生理技术因其具备无创性、可重复性、床旁监测便利性及高时间分辨率的优势,逐渐成为意识障碍评估的关键工具。本文旨在系统梳理脑电图与体感诱发电位在意识障碍诊断及预后中的应用现状,分析其优势与局限性,并探讨未来研究方向。
Abstract: Disorders of consciousness (DoC) are clinically defined as pathological states of disrupted arousal and awareness caused by severe brain injury, encompassing coma, vegetative state/unresponsive wakefulness syndrome (VS/UWS), and minimally conscious state (MCS). As a pivotal research focus in neuroscience, the diagnostic stratification and prognostic stratification of DoC carry substantial implications for evidence-based clinical management, optimized healthcare resource utilization, and targeted family counseling, while remaining a persistent challenge in clinical practice. Conventional behavioral assessment scales (e.g., CRS-R) are critically limited by inherent subjective limitations and elevated misdiagnosis rates, failing to meet modern medicine’s demand for objective and precise diagnostics. Recent advances in multimodal neuroelectrophysiological monitoring—particularly electroencephalography (EEG) and somatosensory evoked potentials (SSEPs), have emerged as critical tools for consciousness assessment due to their non-invasive nature, reproducibility, bedside monitoring feasibility, and high temporal resolution. This article systematically reviews current applications of EEG and SSEPs in the diagnosis and prognosis of DoC, analyzes their strengths and limitations, and explores future research directions.
文章引用:唐云乐, 肖农. 脑电图与体感诱发电位在意识障碍患者诊断及预后评估中的应用[J]. 临床医学进展, 2025, 15(5): 306-313. https://doi.org/10.12677/acm.2025.1551372

参考文献

[1] Threlkeld, Z.D., Bodien, Y.G. and Edlow, B.L. (2025) A Scientific Approach to Diagnosis of Disorders of Consciousness. Handbook of Clinical Neurology, 207, 49-66. [Google Scholar] [CrossRef] [PubMed]
[2] Lin, P. and Yu, H. (2024) Advancing Our Knowledge of Cognition in Disorders of Consciousness: A Critical Revisit. Acta Neurologica Taiwanica, 33, 1-3. [Google Scholar] [CrossRef
[3] Bodien, Y.G., Allanson, J., Cardone, P., Bonhomme, A., Carmona, J., Chatelle, C., et al. (2024) Cognitive Motor Dissociation in Disorders of Consciousness. New England Journal of Medicine, 391, 598-608. [Google Scholar] [CrossRef] [PubMed]
[4] Young, M.J., Edlow, B.L. and Bodien, Y.G. (2024) Covert Consciousness. NeuroRehabilitation, 54, 23-42. [Google Scholar] [CrossRef] [PubMed]
[5] Hoedemaekers, C., Hofmeijer, J. and Horn, J. (2023) Value of EEG in Outcome Prediction of Hypoxic-Ischemic Brain Injury in the ICU: A Narrative Review. Resuscitation, 189, Article ID: 109900. [Google Scholar] [CrossRef] [PubMed]
[6] Leithner, C. and Endisch, C. (2025) Evoked Potentials in Patients with Disorders of Consciousness. Handbook of Clinical Neurology, 207, 147-164. [Google Scholar] [CrossRef] [PubMed]
[7] 郑小春. 基于EEG的慢性意识障碍患者脑不对称性及其与预后的相关性研究[D]: [硕士学位论文]. 广州: 南方医科大学, 2024.
[8] Meiron, O., Barron, J., David, J. and Jaul, E. (2021) Neural Reactivity Parameters of Awareness Predetermine One-Year Survival in Patients with Disorders of Consciousness. Brain Injury, 35, 453-459. [Google Scholar] [CrossRef] [PubMed]
[9] Perera, K., Khan, S., Singh, S., Kromm, J., Wang, M., Sajobi, T., et al. (2021) EEG Patterns and Outcomes after Hypoxic Brain Injury: A Systematic Review and Meta-Analysis. Neurocritical Care, 36, 292-301. [Google Scholar] [CrossRef] [PubMed]
[10] Young, G.B., McLachlan, R.S., Kreeft, J.H. and Demelo, J.D. (1997) An Electroencephalographic Classification for Coma. Canadian Journal of Neurological Sciences/Journal Canadien des Sciences Neurologiques, 24, 320-325. [Google Scholar] [CrossRef] [PubMed]
[11] Synek, V.M. (1988) Prognostically Important EEG Coma Patterns in Diffuse Anoxic and Traumatic Encephalopathies in Adults. Journal of Clinical Neurophysiology, 5, 161-174. [Google Scholar] [CrossRef] [PubMed]
[12] Hofmeijer, J., Beernink, T.M.J., Bosch, F.H., Beishuizen, A., Tjepkema-Cloostermans, M.C. and van Putten, M.J.A.M. (2015) Early EEG Contributes to Multimodal Outcome Prediction of Postanoxic Coma. Neurology, 85, 137-143. [Google Scholar] [CrossRef] [PubMed]
[13] Gaspard, N., Hirsch, L.J., LaRoche, S.M., Hahn, C.D. and Westover, M.B. (2014) Interrater Agreement for Critical Care EEG Terminology. Epilepsia, 55, 1366-1373. [Google Scholar] [CrossRef] [PubMed]
[14] Sethi, N.K. (2016) Standardized EEG Interpretation Accurately Predicts Prognosis after Cardiac Arrest. Neurology, 87, 1631-1631. [Google Scholar] [CrossRef] [PubMed]
[15] Ballanti, S., Campagnini, S., Liuzzi, P., Hakiki, B., Scarpino, M., Macchi, C., et al. (2022) EEG-Based Methods for Recovery Prognosis of Patients with Disorders of Consciousness: A Systematic Review. Clinical Neurophysiology, 144, 98-114. [Google Scholar] [CrossRef] [PubMed]
[16] Wang, J., Chen, X., Zhou, L., Liu, Z., Xia, Y., You, J., et al. (2022) Assessment of Electroencephalography and Event-Related Potentials in Unresponsive Patients with Brain Injury. Neurophysiologie Clinique, 52, 384-393. [Google Scholar] [CrossRef] [PubMed]
[17] Gottshall, J.L. and Rossi Sebastiano, D. (2020) Sleep in Disorders of Consciousness: Diagnostic, Prognostic, and Therapeutic Considerations. Current Opinion in Neurology, 33, 684-690. [Google Scholar] [CrossRef] [PubMed]
[18] Kondziella, D., Bender, A., Diserens, K., van Erp, W., Estraneo, A., Formisano, R., et al. (2020) European Academy of Neurology Guideline on the Diagnosis of Coma and Other Disorders of Consciousness. European Journal of Neurology, 27, 741-756. [Google Scholar] [CrossRef] [PubMed]
[19] Williams Roberson, S., Azeez, N.A., Fulton, J.N., Zhang, K.C., Lee, A.X.T., Ye, F., et al. (2023) Quantitative EEG Signatures of Delirium and Coma in Mechanically Ventilated ICU Patients. Clinical Neurophysiology, 146, 40-48. [Google Scholar] [CrossRef] [PubMed]
[20] Lutkenhoff, E.S., Nigri, A., Rossi Sebastiano, D., Sattin, D., Visani, E., Rosazza, C., et al. (2020) EEG Power Spectra and Subcortical Pathology in Chronic Disorders of Consciousness. Psychological Medicine, 52, 1491-1500. [Google Scholar] [CrossRef] [PubMed]
[21] Liu, Y., Zeng, W., Pan, N., Xia, X., Huang, Y. and He, J. (2023) EEG Complexity Correlates with Residual Consciousness Level of Disorders of Consciousness. BMC Neurology, 23, Article No. 140. [Google Scholar] [CrossRef] [PubMed]
[22] 刘艳. 静息态脑电复杂度对意识障碍患者预后判别的价值研究[D]: [硕士学位论文]. 西安: 空军军医大学, 2023.
[23] Ma, X., Qi, Y., Xu, C., Weng, Y., Yu, J., Sun, X., et al. (2024) How Well Do Neural Signatures of Resting‐State EEG Detect Consciousness? A Large‐scale Clinical Study. Human Brain Mapping, 45, e26586. [Google Scholar] [CrossRef] [PubMed]
[24] Wu, Y., Li, Z., Qu, R., Wang, Y., Li, Z., Wang, L., et al. (2023) Electroencephalogram-Based Brain Connectivity Analysis in Prolonged Disorders of Consciousness. Neural Plasticity, 2023, Article ID: 4142053. [Google Scholar] [CrossRef] [PubMed]
[25] Duclos, C., Maschke, C., Mahdid, Y., Berkun, K., Castanheira, J.D.S., Tarnal, V., et al. (2021) Differential Classification of States of Consciousness Using Envelope-and Phase-Based Functional Connectivity. NeuroImage, 237, Article ID: 118171. [Google Scholar] [CrossRef] [PubMed]
[26] Ridha, M., Kumar, A. and Claassen, J. (2025) Electrophysiology in Disorders of Consciousness. Handbook of Clinical Neurology, 207, 129-146. [Google Scholar] [CrossRef] [PubMed]
[27] Bai, Y., Yang, L., Meng, X., Huang, Y., Wang, Q., Gong, A., et al. (2024) Breakdown of Effective Information Flow in Disorders of Consciousness: Insights from TMS-EEG. Brain Stimulation, 17, 533-542. [Google Scholar] [CrossRef] [PubMed]
[28] Sandroni, C., Grippo, A. and Westhall, E. (2023) The Role of the Electroencephalogram and Evoked Potentials after Cardiac Arrest. Current Opinion in Critical Care, 29, 199-207. [Google Scholar] [CrossRef] [PubMed]
[29] 刘华, 谭亚琼, 胡继红,等. 体感诱发电位联合改良昏迷恢复量表对儿童重症脑损伤恢复期意识障碍的预后评价[J]. 中国实用神经疾病杂志, 2023, 26(1): 67-71.
[30] Sandroni, C., D’Arrigo, S., Cacciola, S., Hoedemaekers, C.W.E., Kamps, M.J.A., Oddo, M., et al. (2020) Prediction of Poor Neurological Outcome in Comatose Survivors of Cardiac Arrest: A Systematic Review. Intensive Care Medicine, 46, 1803-1851. [Google Scholar] [CrossRef] [PubMed]
[31] Aalberts, N., Westhall, E., Johnsen, B., Hahn, K., Kenda, M., Cronberg, T., et al. (2023) Cortical Somatosensory Evoked Potential Amplitudes and Clinical Outcome after Cardiac Arrest: A Retrospective Multicenter Study. Journal of Neurology, 270, 5999-6009. [Google Scholar] [CrossRef] [PubMed]
[32] Pruvost-Robieux, E., Marchi, A., Martinelli, I., Bouchereau, E. and Gavaret, M. (2021) Evoked and Event-Related Potentials as Biomarkers of Consciousness State and Recovery. Journal of Clinical Neurophysiology, 39, 22-31. [Google Scholar] [CrossRef] [PubMed]
[33] Lachance, B., Wang, Z., Badjatia, N. and Jia, X. (2020) Somatosensory Evoked Potentials and Neuroprognostication after Cardiac Arrest. Neurocritical Care, 32, 847-857. [Google Scholar] [CrossRef] [PubMed]
[34] Wang, J., Lai, Q., Han, J., Qin, P. and Wu, H. (2024) Neuroimaging Biomarkers for the Diagnosis and Prognosis of Patients with Disorders of Consciousness. Brain Research, 1843, Article ID: 149133. [Google Scholar] [CrossRef] [PubMed]
[35] 王瑾, 陈道朋, 冯应君, 等. 多模态神经电生理指标对意识障碍的预后评估价值[J]. 生命科学仪器, 2024, 22(3): 149-153.
[36] Song, M., Yang, Y., Yang, Z., Cui, Y., Yu, S., He, J., et al. (2020) Prognostic Models for Prolonged Disorders of Consciousness: An Integrative Review. Cellular and Molecular Life Sciences, 77, 3945-3961. [Google Scholar] [CrossRef] [PubMed]
[37] Lee, M. and Laureys, S. (2024) Artificial Intelligence and Machine Learning in Disorders of Consciousness. Current Opinion in Neurology, 37, 614-620. [Google Scholar] [CrossRef] [PubMed]
[38] Candia‐Rivera, D. and Machado, C. (2023) Multidimensional Assessment of Heartbeat‐evoked Responses in Disorders of Consciousness. European Journal of Neuroscience, 58, 3098-3110. [Google Scholar] [CrossRef] [PubMed]
[39] Liuzzi, P., Campagnini, S., Hakiki, B., Burali, R., Scarpino, M., Macchi, C., et al. (2023) Heart Rate Variability for the Evaluation of Patients with Disorders of Consciousness. Clinical Neurophysiology, 150, 31-39. [Google Scholar] [CrossRef] [PubMed]
[40] Smith, A.E. and Friess, S.H. (2020) Neurological Prognostication in Children after Cardiac Arrest. Pediatric Neurology, 108, 13-22. [Google Scholar] [CrossRef] [PubMed]