Gu Youquan, Chen Jun, Lu Yaqin, Pan Suyue
Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou, China Department of Neurology, First Hospital of Lanzhou University, Lanzhou, China.
Department of Neurology, First Hospital of Lanzhou University, Lanzhou, China.
Clin EEG Neurosci. 2016 Apr;47(2):113-7. doi: 10.1177/1550059414543796. Epub 2014 Dec 16.
Clinically, predicting the progression of mild cognitive impairment (MCI) and diagnosing dementia in Parkinson's disease (PD) are difficult. This study aims to explore an integrative electroencephalography (EEG) frequency power that could be used to predict the progression of MCI in PD patients. Twenty-six PD patients, in this study, were divided into the mild cognitive impairment group (PDMCI, 17 patients) and dementia group (PDD, 9 patients) according to cognitive performance. Beta peak frequency, alpha relative power, and alpha/theta power were recorded and analyzed for the prediction. Mini Mental State Examination (MMSE) scores at initiation, in the first year, and in the second year were examined. The sensitivity, specificity, positive predictive value, Matthew correlation coefficient, and positive likelihood ratio were calculated in both the integrative EEG biomarkers and single best biomarker. Of the 17 patients with MCI for 2 years, 6 progressed to dementia. Integrative EEG biomarkers, mainly associated with beta peak frequency, can predict conversion from MCI to dementia. These biomarkers had sensitivity of 82% and specificity of 78%, compared with sensitivity of 61% and specificity of 58% of the beta peak frequency. In conclusion, the integrative EEG frequency powers were more sensitive and specific to MCI progression in PD patients.
临床上,预测帕金森病(PD)患者轻度认知障碍(MCI)的进展并诊断痴呆症具有一定难度。本研究旨在探索一种综合脑电图(EEG)频率功率,用于预测PD患者MCI的进展。本研究中,26例PD患者根据认知表现分为轻度认知障碍组(PD - MCI,17例)和痴呆组(PDD,9例)。记录并分析β峰频率、α相对功率和α/θ功率以进行预测。检测了起始时、第1年和第2年的简易精神状态检查表(MMSE)评分。计算了综合EEG生物标志物和单一最佳生物标志物的敏感性、特异性、阳性预测值、马修相关系数和阳性似然比。在17例MCI持续2年的患者中,6例进展为痴呆症。主要与β峰频率相关的综合EEG生物标志物可预测MCI向痴呆症的转化。这些生物标志物的敏感性为82%,特异性为78%,而β峰频率的敏感性为61%,特异性为58%。总之,综合EEG频率功率对PD患者MCI进展更敏感且更具特异性。