Anticholinergic Medication Burden in Parkinson's Disease Outpatients.

Parkinson’s disease Parkinson’s disease dementia anticholinergic medications cholinesterase inhibitors

Journal

Journal of Parkinson's disease
ISSN: 1877-718X
Titre abrégé: J Parkinsons Dis
Pays: Netherlands
ID NLM: 101567362

Informations de publication

Date de publication:
2022
Historique:
pubmed: 23 11 2021
medline: 28 4 2022
entrez: 22 11 2021
Statut: ppublish

Résumé

Individuals with Parkinson's disease (PD) may be especially vulnerable to future cognitive decline from anticholinergic medications. 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. 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. 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). 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.

Sections du résumé

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.

Identifiants

pubmed: 34806617
pii: JPD212769
doi: 10.3233/JPD-212769
pmc: PMC9602053
mid: NIHMS1842185
doi:

Substances chimiques

Antipsychotic Agents 0
Cholinergic Antagonists 0
Cholinesterase Inhibitors 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

599-606

Subventions

Organisme : NCATS NIH HHS
ID : UL1 TR002649
Pays : United States

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Auteurs

Huma Nawaz (H)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.

Lana Sargent (L)

School of Nursing, Virginia Commonwealth University, Richmond, VA, USA.
Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA.
Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA.
Institute for Inclusion, Inquiry & Innovation (iCubed): Health & Wellness in Aging Populations Core, Richmond, VA, USA.

Helengrace Quilon (H)

Virginia Commonwealth University, Richmond, VA, USA.

Leslie J Cloud (LJ)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.

Claudia M Testa (CM)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.

Jon D Snider (JD)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.

Sarah K Lageman (SK)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.
Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA.

Mark S Baron (MS)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.
Southeast Veterans Affairs Parkinson's Disease Research, Education and Clinical Center (PADRECC), Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, VA, USA.

Brian D Berman (BD)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.

Kristin Zimmerman (K)

Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA.

Elvin T Price (ET)

Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA.
Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA.
Institute for Inclusion, Inquiry & Innovation (iCubed): Health & Wellness in Aging Populations Core, Richmond, VA, USA.

Nitai D Mukhopadhyay (ND)

Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.

Matthew J Barrett (MJ)

Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.

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Classifications MeSH