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利用前额叶脑电图和事件相关电位预测痴呆症

Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential.

作者信息

Doan Dieu Ni Thi, Ku Boncho, Choi Jungmi, Oh Miae, Kim Kahye, Cha Wonseok, Kim Jaeuk U

机构信息

Korea Institute of Oriental Medicine, Daejeon, South Korea.

Korean Convergence Medicine, University of Science and Technology, Daejeon, South Korea.

出版信息

Front Aging Neurosci. 2021 Apr 13;13:659817. doi: 10.3389/fnagi.2021.659817. eCollection 2021.

Abstract

: To examine whether prefrontal electroencephalography (EEG) can be used for screening dementia. : We estimated the global cognitive decline using the results of Mini-Mental Status Examination (MMSE), measurements of brain activity from resting-state EEG, responses elicited by auditory stimulation [sensory event-related potential (ERP)], and selective attention tasks (selective-attention ERP) from 122 elderly participants (dementia, 35; control, 87). We investigated that the association between MMSE and each EEG/ERP variable by using Pearson's correlation coefficient and performing univariate linear regression analysis. Kernel density estimation was used to examine the distribution of each EEG/ERP variable in the dementia and non-dementia groups. Both Univariate and multiple logistic regression analyses with the estimated odds ratios were conducted to assess the associations between the EEG/ERP variables and dementia prevalence. To develop the predictive models, five-fold cross-validation was applied to multiple classification algorithms. : Most prefrontal EEG/ERP variables, previously known to be associated with cognitive decline, show correlations with the MMSE score (strongest correlation has = 0.68). Although variables such as the frontal asymmetry of the resting-state EEG are not well correlated with the MMSE score, they indicate risk factors for dementia. The selective-attention ERP and resting-state EEG variables outperform the MMSE scores in dementia prediction (areas under the receiver operating characteristic curve of 0.891, 0.824, and 0.803, respectively). In addition, combining EEG/ERP variables and MMSE scores improves the model predictive performance, whereas adding demographic risk factors do not improve the prediction accuracy. : Prefrontal EEG markers outperform MMSE scores in predicting dementia, and additional prediction accuracy is expected when combining them with MMSE scores. : Prefrontal EEG is effective for screening dementia when used independently or in combination with MMSE.

摘要

目的

探讨前额叶脑电图(EEG)能否用于痴呆筛查。

方法

我们使用简易精神状态检查表(MMSE)的结果、静息态EEG的脑活动测量值、听觉刺激诱发的反应[感觉事件相关电位(ERP)]以及122名老年参与者(痴呆患者35名,对照组87名)的选择性注意任务(选择性注意ERP)来评估整体认知衰退情况。我们通过使用Pearson相关系数并进行单变量线性回归分析,研究MMSE与每个EEG/ERP变量之间的关联。使用核密度估计来检查痴呆组和非痴呆组中每个EEG/ERP变量的分布情况。进行单变量和多变量逻辑回归分析,并估计优势比,以评估EEG/ERP变量与痴呆患病率之间的关联。为了开发预测模型,将五折交叉验证应用于多种分类算法。

结果

大多数先前已知与认知衰退相关的前额叶EEG/ERP变量与MMSE评分存在相关性(最强相关性r = 0.68)。虽然静息态EEG的额叶不对称等变量与MMSE评分的相关性不佳,但它们表明是痴呆的危险因素。在痴呆预测方面,选择性注意ERP和静息态EEG变量优于MMSE评分(受试者操作特征曲线下面积分别为0.891、0.824和0.803)。此外,将EEG/ERP变量和MMSE评分相结合可提高模型预测性能,而添加人口统计学危险因素并不能提高预测准确性。

结论

前额叶EEG标志物在预测痴呆方面优于MMSE评分,将它们与MMSE评分相结合时有望提高预测准确性。

结论

前额叶EEG单独使用或与MMSE联合使用时,对痴呆筛查有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bdb/8077968/450e7880850b/fnagi-13-659817-g0001.jpg

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