Abstract
Objective: We aimed to determine whether the combination of two parameters: (a) score of axial impairment and limb rigidity (SAILR) with (b) EEG global relative median power in the frequency range theta 4–8 Hz (GRMPT) predicted cognitive outcome in patients with Parkinson's disease (PD) better than each of these measures alone.Methods: 47 non-demented patients with PD were examined and re-examined after 3 years. At both time-points, the patients underwent a comprehensive neuropsychological and neurological assessment and EEG in eyes-closed resting-state condition. The results of cognitive tests were normalized and individually summarized to obtain a “global cognitive score” (GCS). Change of GCS was used to represent cognitive changes over time. GRMPT and SAILR was used for further analysis. Linear regression models were calculated.Results: GRMPT and SAILR independently predicted cognitive change. Combination of GRMPT and SAILR improved the significance of the regression model as compared to using each of these measures alone. GRMPT and SAILR only slightly correlate between each other.Conclusion: The combination of axial signs and rigidity with quantitative EEG improves early identification of patients with PD prone to severe cognitive decline. GRMPT and SAILR seem to reflect different disease mechanisms.Significance Combination of EEG and axial motor impairment assessment may be a valuable marker in the cognitive prognosis of PD.
Highlights
Since dementia in Parkinson’s Disease (PD) dramatically worsens the course of the disease (Levy et al, 2002; Aarsland and Kurz, 2010; Aarsland et al, 2017) early and correct identification of the patients at high risk of developing dementia over the long term course of the disease is highly relevant
Combination of EEG and axial motor impairment assessment may be a valuable marker in the cognitive prognosis of PD
Some researchers suggested that a combination of different prognostic markers—sometimes this combination is referred to as ≪composite marker≫—allows to identify patients with PD who have a risk of dementia, better than a single marker (Sonnen et al, 2008; Shi et al, 2010; Liu et al, 2017)
Summary
Since dementia in Parkinson’s Disease (PD) dramatically worsens the course of the disease (Levy et al, 2002; Aarsland and Kurz, 2010; Aarsland et al, 2017) early and correct identification of the patients at high risk of developing dementia over the long term course of the disease is highly relevant. Some researchers suggested that a combination of different prognostic markers—sometimes this combination is referred to as ≪composite marker≫—allows to identify patients with PD who have a risk of dementia, better than a single marker (Sonnen et al, 2008; Shi et al, 2010; Liu et al, 2017) To explain this finding the researchers made the assumption that the analysis of various pathological aspects of PD (e.g., genetic susceptibility, protein overproduction and accumulation, cortical function etc.) increases the precision of calculation of the dementia risk. Evaluation of body temperature, chest X-Ray, and blood parameters will surely better predict the course of pneumonia than the analysis of body temperature alone Another important issue in the identification and selection of component markers is avoiding multicollinearity. Such redundant factors significantly impair the precision of the statistical calculation (for details, see Allen, 1997)
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