Abstract
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.
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