Session Information
Date: Wednesday, June 22, 2016
Session Title: Parkinson's disease: Cognition
Session Time: 12:00pm-1:30pm
Location: Exhibit Hall located in Hall B, Level 2
Objective: To investigate whether changes in EEG power spectra could predict development of dementia in Parkinson’s disease (PD-D).
Background: Different research groups have reported, that EEG slowing is associated with cognitive decline in PD.
Methods: Patients with PD were screened for selection criteria: idiopathic Parkinson’s disease (PD), absence of major cognitive and psychiatric dysfunctions according to Diagnostic and Statistical Manual of mental disorders IV, MMSE ≥24. A sample of 35 patients was followed-up (median ⦥: age 67 [31-84] years, education 15 [9-20] years, disease duration 5 [1-20] years, MMSE 29 [24-30], UPDRS-III 16 [0-50], Levodopa equivalent 700 [150-2130] mg/day; males: 65%. The patients were investigated at baseline and after 36 months for the outcome: development of PD-D. Clinical examinations included evaluations: motor (UPDRS-III), psychiatric (Beck Depression Inventory), medication (Levodopa equivalent), neuropsychological test battery (36 tests); high resolution EEG recording was performed, and global relative spectral powers calculated: delta (1-3.9 Hz), theta (4-7.9 Hz), alpha1 (8-9.9 Hz), alpha2 (10-12.9 Hz) and beta (13-30 Hz). Predictive performance of power spectra over developing PD-D in 3 years was evaluated with Spearman rank correlation coefficient and multiple linear regressions.
Results: Five patients developed PD-D after three years (14.3%). Development of PD-D correlated best with theta power at baseline (rho=0.59, p<0.01). Multiple regression model showed that theta power significantly predicted PD-D (adjusted R squared=0.58, p<0.01).
Conclusions: Global relative EEG theta power has good predictive performance for developing PD-D over three years. Due to the relatively small sample and short follow-up, further studies to identify markers of PD-D and to improve the predictive performance of EEG power spectra are required.
To cite this abstract in AMA style:
V.V. Cozac, M. Chaturvedi, U. Gschwandtner, F. Hatz, A. Meyer, K. Nowak, R. Sturzenegger, P. Fuhr. Predictive performance of EEG theta spectral power over developing dementia in Parkinson’s disease [abstract]. Mov Disord. 2016; 31 (suppl 2). https://www.mdsabstracts.org/abstract/predictive-performance-of-eeg-theta-spectral-power-over-developing-dementia-in-parkinsons-disease/. Accessed May 18, 2025.« Back to 2016 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/predictive-performance-of-eeg-theta-spectral-power-over-developing-dementia-in-parkinsons-disease/