{"title":"意识障碍患者的脑电图微状态分析及其临床意义。","authors":"Eren Toplutaş, Fatma Aydın, Lütfü Hanoğlu","doi":"10.1007/s10548-023-00939-y","DOIUrl":null,"url":null,"abstract":"<p><p>Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.</p>","PeriodicalId":55329,"journal":{"name":"Brain Topography","volume":" ","pages":"377-387"},"PeriodicalIF":2.3000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance.\",\"authors\":\"Eren Toplutaş, Fatma Aydın, Lütfü Hanoğlu\",\"doi\":\"10.1007/s10548-023-00939-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.</p>\",\"PeriodicalId\":55329,\"journal\":{\"name\":\"Brain Topography\",\"volume\":\" \",\"pages\":\"377-387\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brain Topography\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10548-023-00939-y\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/2/3 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain Topography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10548-023-00939-y","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/2/3 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
摘要
意识障碍分为两大类,如植物人和微意识状态。我们需要能够正确识别植物人和微意识状态患者的客观测量方法。脑电图微状态分析是一种很有前途的方法,我们认为这种方法有可能有效检查不同意识阶段的大脑静息状态活动,从而正确识别植物人和微意识状态患者。因此,我们试图通过意识障碍患者的静息状态脑电图来确定临床评估量表和微状态特征。我们的前瞻性观察研究包括 28 名意识障碍患者。对照组包括 18 名具有适当脑电图数据的健康受试者。我们使用患者行为量表进行了临床评估。我们还使用微状态分析法对脑电图进行了分析。在我们的研究中,植物人和微意识状态患者的微状态 D 覆盖率有很大不同。此外,微状态 D 的特征与临床量表评分之间也存在密切联系。因此,我们证明了微状态 D 是代表意识水平的最准确参数。微状态分析似乎是未来用于意识障碍患者的诊断、随访和治疗反应的有力选择。
EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance.
Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.
期刊介绍:
Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.