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通过脑电图分析比较帕金森病痴呆患者与路易体痴呆患者的脑活动

Comparison of Brain Activity between Patients with Parkinson Disease Dementia and Patients Affected by Dementia with Lewy Body through EEG Analysis.

作者信息

Abbood Sharara Fadhil, Abdul-Rasul Israa Jawad, Al-Zughaibi Amaal Sahib, Al-Shukri Hamzah H Kzar, Rabee Fadak B, Fadhil Zainab A, Radhi Zainab A A

机构信息

Department of Chemistry and Biochemistry, College of Medicine, University of Karbala, Karbala, Iraq.

Pharmacy Department, AlSafwa University College, Karbala, Iraq.

出版信息

Iran J Psychiatry. 2024 Oct;19(4):346-355. doi: 10.18502/ijps.v19i4.16548.

DOI:10.18502/ijps.v19i4.16548
PMID:40589837
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12206469/
Abstract

Parkinson's disease dementia (PDD) and Dementia with Lewy bodies (DLB) are two syndromes categorized under synucleinopathy, sharing comparable symptoms. The identification of biomarkers would offer an accurate approach for improved diagnosis, treatment, and monitoring of treatment efficacy for these distinct forms of dementia. This study utilized spectral analysis and nonlinear dynamic analysis to compare electroencephalogram (EEG) characteristics between PDD and DLB patients. EEG data was collected from 30 PDD patients, 36 DLB patients, and 36 healthy subjects at rest. Following a conditioning phase to minimize noise and eliminate artifacts, we derived spectral and complexity features using Welch's method and sample entropy. Analysis of variance with repeated measures was performed to compare spectral features and nonlinear dynamics of brain activity between the groups. Post hoc comparison showed that in the control group, the power of delta and theta bands was lower and the power of alpha and beta bands was higher than in patients with PDD and DLB. (P < 0.05). In the theta and alpha bands, the PDD group showed greater power than the DLB group (P < 0.05). Furthermore, there was a significant main effect of diagnosis (F = 4.67, P = 0.007), and also the diagnosis by region interaction for complexity values (F = 4.58, P = 0.009). Post hoc analysis showed that the EEG complexity of the control group was significantly higher than that of the PDD and DLB groups in the frontal, central, temporal and parietal regions (P < 0.05). Moreover, the EEG complexity of the PDD group was significantly higher than that of the DLB group in the central, temporal and parietal regions (P < 0.05). Although both PDD and DLB had almost similar patterns compared to the control group, they showed differences in the EEG power spectrum and its nonlinear dynamics. Our findings indicated marked diffuse slowing and lower cortical complexity or activity in DLB patients compared to PDD in all regions, especially in the central, temporal and parietal areas.

摘要

帕金森病痴呆(PDD)和路易体痴呆(DLB)是两种归类于突触核蛋白病的综合征,具有相似的症状。生物标志物的识别将为这些不同形式痴呆的诊断、治疗及治疗效果监测提供一种准确的方法。本研究利用频谱分析和非线性动力学分析来比较PDD和DLB患者的脑电图(EEG)特征。在静息状态下,从30例PDD患者、36例DLB患者和36名健康受试者收集EEG数据。经过一个调节阶段以最小化噪声并消除伪迹后,我们使用韦尔奇方法和样本熵得出频谱和复杂性特征。采用重复测量方差分析来比较各组之间大脑活动的频谱特征和非线性动力学。事后比较表明,在对照组中,δ波和θ波频段的功率低于PDD和DLB患者,而α波和β波频段的功率高于PDD和DLB患者(P<0.05)。在θ波和α波频段,PDD组的功率高于DLB组(P<0.05)。此外,诊断存在显著的主效应(F = 4.67,P = 0.007),并且复杂性值的诊断与区域存在交互作用(F = 4.58,P = 0.009)。事后分析表明,对照组在额叶、中央、颞叶和顶叶区域的EEG复杂性显著高于PDD组和DLB组(P<0.05)。此外,PDD组在中央、颞叶和顶叶区域的EEG复杂性显著高于DLB组(P<0.05)。尽管与对照组相比,PDD和DLB的模式几乎相似,但它们在EEG功率谱及其非线性动力学方面存在差异。我们的研究结果表明,与PDD相比,DLB患者在所有区域,尤其是在中央、颞叶和顶叶区域,存在明显的弥漫性减慢以及较低的皮质复杂性或活动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5daf/12206469/1bda50501176/IJPS-19-346-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5daf/12206469/d415847a3dba/IJPS-19-346-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5daf/12206469/1bda50501176/IJPS-19-346-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5daf/12206469/d415847a3dba/IJPS-19-346-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5daf/12206469/1bda50501176/IJPS-19-346-g002.jpg

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本文引用的文献

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Health Sci Rep. 2024 Mar 31;7(4):e2019. doi: 10.1002/hsr2.2019. eCollection 2024 Apr.
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Subclinical Epileptiform Activity in Dementia with Lewy Bodies.路易体痴呆中的亚临床癫痫样活动。
Mov Disord. 2023 Oct;38(10):1861-1870. doi: 10.1002/mds.29531. Epub 2023 Jul 11.
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An Overview of Bipolar Disorder Diagnosis Using Machine Learning Approaches: Clinical Opportunities and Challenges.使用机器学习方法进行双相情感障碍诊断概述:临床机遇与挑战
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Possible Neuropathological Mechanisms Underlying the Increased Complexity of Brain Electrical Activity in Schizophrenia: A Computational Study.精神分裂症患者脑电活动复杂性增加背后可能的神经病理学机制:一项计算研究
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Cognitive and Motor Decline in Dementia with Lewy Bodies and Parkinson's Disease Dementia.路易体痴呆和帕金森病痴呆中的认知与运动衰退
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