The relative importance of antimuscarinic anticholinergic medications for Parkinson's disease (PD) declined after the introduction of levodopa, such that anticholinergic medications are now much more likely to be prescribed for clinical indications other than parkinsonism. Recent studies have found an association between anticholinergic medication exposure and future risk of dementia in older individuals and those with PD. These findings provide a further reason to avoid the use of anticholinergic medications to treat motor symptoms of PD. More importantly, they raise the question of whether one of the goals of PD treatment should be to deprescribe all medications with anticholinergic properties, regardless of their indication, to reduce dementia risk. In this review, we discuss the use of anticholinergic medications in PD, the evidence supporting the association between anticholinergic medications and future dementia risk, and the potential implications of these findings for clinical care in PD.

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Background: Individuals with Parkinson’s disease (PD) may be especially vulnerable to future cognitive decline from anticholinergic medications. Objective: To characterize anticholinergic medication burden, determine the co-occurrence of anticholinergic and cholinesterase inhibitors, and to assess the correlations among anticholinergic burden scales in PD outpatients. Methods: We studied 670 PD outpatients enrolled in a clinic registry between 2012 and 2020. Anticholinergic burden was measured with the Anticholinergic Cognitive Burden Scale (ACB), Anticholinergic Drug Scale (ADS), Anticholinergic Risk Scale (ARS), and Drug Burden Index-Anticholinergic component (DBI-Ach). Correlations between scales were assessed with weighted kappa coefficients. Results: Between 31.5 to 46.3% of PD patients were taking medications with anticholinergic properties. Among the scales applied, the ACB produced the highest prevalence of medications with anticholinergic properties (46.3%). Considering only medications with definite anticholinergic activity (scores of 2 or 3 on ACB, ADS, or ARS), the most common anticholinergic drug classes were antiparkinsonian (8.2%), antipsychotic (6.4%), and urological (3.3%) medications. Cholinesterase inhibitors and medications with anticholinergic properties were co-prescribed to 5.4% of the total cohort. The most highly correlated scales were ACB and ADS (κ= 0.71), ACB and ARS (κ= 0.67), and ADS and ARS (κ= 0.55). Conclusion: A high proportion of PD patients (20%) were either taking antiparkinsonian, urological, or antipsychotic anticholinergic medications or were co-prescribed anticholinergic medications and cholinesterase inhibitors. By virtue of its detection of a high prevalence of anticholinergic medication usage and its high correlation with other scales, our data support use of the ACB scale to assess anticholinergic burden in PD patients.

Background: Cholinergic nucleus 4 (Ch4) degeneration is associated with cognitive impairment in Parkinson's disease and dementia with Lewy bodies, but it is unknown if Ch4 degeneration is also present in isolated rapid eye movement sleep behavior disorder (iRBD). Objective: The aim was to determine if there is evidence of Ch4 degeneration in patients with iRBD and if it is associated with cognitive impairment. Methods: We analyzed the clinical and neuropsychological data of 35 iRBD patients and 35 age-and sex-matched healthy controls. Regional gray matter density (GMD) was calculated for Ch4 using probabilistic maps applied to brain magnetic resonance imaging (MRI). Results: Ch4 GMD was significantly lower in the iRBD group compared to controls (0.417 vs. 0.441, P = 0.02). Ch4 GMD was also found to be a significant predictor of letter number sequencing (β-coefficient = 58.31, P = 0.026, 95% confidence interval [7.47, 109.15]), a measure of working memory. Conclusions: iRBD is associated with Ch4 degeneration, and Ch4 degeneration in iRBD is associated with impairment in working memory.

Objective: To determine the minimum duration of electroencephalography (EEG) data necessary to differentiate EEG features of Lewy body dementia (LBD), that is, dementia with Lewy bodies and Parkinson disease dementia, from non-LBD patients, that is, Alzheimer disease and Parkinson disease.Methods: We performed quantitative EEG analysis for 16 LBD and 14 non-LBD patients. After artifact removal, a fast Fourier transform was performed on 90, 60, and thirty 2-second epochs to derive dominant frequency; dominant frequency variability; and dominant frequency prevalence.Results: In LBD patients, there were no significant differences in EEG features derived from 90, 60, and thirty 2-second epochs (all P > 0.05). There were no significant differences in EEG features derived from 3 different groups of thirty 2-second epochs (all P > 0.05). When analyzing EEG features derived from ninety 2-second epochs, we found that LBD had significantly reduced dominant frequency, reduced dominant frequency variability, and reduced dominant frequency prevalence alpha compared with the non-LBD group (all P < 0.05). These same differences were observed between the LBD and non-LBD groups when analyzing thirty 2-second epochs.Conclusions: There were no differences in EEG features derived from 1 minute versus 3 minutes of EEG data, and both durations of EEG data equally differentiated LBD from non-LBD.