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Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease

INTRODUCTION: Cognitive decline is common in Parkinson’s disease (PD). Calculating personalized risk of cognitive decline in PD would allow for appropriate counseling, early intervention with available treatments, and inclusion in disease-modifying trials. METHODS: Data were from the Parkinson’s Pro...

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Autores principales: Carlisle, Tara C., Medina, Luis D., Holden, Samantha K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628974/
https://www.ncbi.nlm.nih.gov/pubmed/37942138
http://dx.doi.org/10.3389/fnins.2023.1278817
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author Carlisle, Tara C.
Medina, Luis D.
Holden, Samantha K.
author_facet Carlisle, Tara C.
Medina, Luis D.
Holden, Samantha K.
author_sort Carlisle, Tara C.
collection PubMed
description INTRODUCTION: Cognitive decline is common in Parkinson’s disease (PD). Calculating personalized risk of cognitive decline in PD would allow for appropriate counseling, early intervention with available treatments, and inclusion in disease-modifying trials. METHODS: Data were from the Parkinson’s Progression Markers Initiative de novo cohort. Baseline scores were calculated for Lifestyle for Brain Health (LIBRA) and the Montreal Parkinson Risk of Dementia Scale (MoPaRDS) per prior literature and preliminary Parkinson’s disease Risk Estimator for Decline In Cognition Tool (pPREDICT) by attributing a point for fourteen posited risk factors. Baseline and 5-year follow-up composite cognitive scores (CCSs) were calculated from a neuropsychological battery and used to define cognitive decliners (PD-decline) versus maintainers (PD-maintain). RESULTS: The PD-decline group (n = 44) had higher LIBRA (6.76 ± 0.57, p < 0.05), MoPaRDS (2.45 ± 1.41, p < 0.05) and pPREDICT (4.52 ± 1.66, p < 0.05) scores compared to the PD-maintain group (n = 263; LIBRA 4.98 ± 0.20, MoPaRDS 1.68 ± 1.16, pPREDICT 3.38 ± 1.69). Area-under-the-curve (AUC) for LIBRA was 0.64 (95% confidence interval [CI], 0.55–0.73), MoPaRDS was 0.66 (95% CI, 0.58–0.75) and for pPREDICT was 0.68 (95% CI, 0.61–0.76). In linear regression analyses, LIBRA (p < 0.05), MoPaRDS (p < 0.05) and pPREDICT (p < 0.05) predicted change in CCS. Only age stratified by sex (p < 0.05) contributed significantly to the model for LIBRA. Age and presence of hallucinations (p < 0.05) contributed significantly to the model for MoPaRDS. Male sex, older age, excessive daytime sleepiness, and moderate–severe motor symptoms (all p < 0.05) contributed significantly to the model for pPREDICT. CONCLUSION: Although MoPaRDS is a PD-specific tool for predicting cognitive decline relying on only clinical features, it does not focus on potentially modifiable risk factors. LIBRA does focus on potentially modifiable risk factors and is associated with prediction of all-cause dementia in some populations, but pPREDICT potentially demonstrates improved performance in cognitive decline risk calculation in individuals with PD and may identify actionable risk factors. As pPREDICT incorporates multiple potentially modifiable risk factors that can be obtained easily in the clinical setting, it is a first step in developing an easily assessable tool for a personalized approach to reduce dementia risk in people with PD.
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spelling pubmed-106289742023-11-08 Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease Carlisle, Tara C. Medina, Luis D. Holden, Samantha K. Front Neurosci Neuroscience INTRODUCTION: Cognitive decline is common in Parkinson’s disease (PD). Calculating personalized risk of cognitive decline in PD would allow for appropriate counseling, early intervention with available treatments, and inclusion in disease-modifying trials. METHODS: Data were from the Parkinson’s Progression Markers Initiative de novo cohort. Baseline scores were calculated for Lifestyle for Brain Health (LIBRA) and the Montreal Parkinson Risk of Dementia Scale (MoPaRDS) per prior literature and preliminary Parkinson’s disease Risk Estimator for Decline In Cognition Tool (pPREDICT) by attributing a point for fourteen posited risk factors. Baseline and 5-year follow-up composite cognitive scores (CCSs) were calculated from a neuropsychological battery and used to define cognitive decliners (PD-decline) versus maintainers (PD-maintain). RESULTS: The PD-decline group (n = 44) had higher LIBRA (6.76 ± 0.57, p < 0.05), MoPaRDS (2.45 ± 1.41, p < 0.05) and pPREDICT (4.52 ± 1.66, p < 0.05) scores compared to the PD-maintain group (n = 263; LIBRA 4.98 ± 0.20, MoPaRDS 1.68 ± 1.16, pPREDICT 3.38 ± 1.69). Area-under-the-curve (AUC) for LIBRA was 0.64 (95% confidence interval [CI], 0.55–0.73), MoPaRDS was 0.66 (95% CI, 0.58–0.75) and for pPREDICT was 0.68 (95% CI, 0.61–0.76). In linear regression analyses, LIBRA (p < 0.05), MoPaRDS (p < 0.05) and pPREDICT (p < 0.05) predicted change in CCS. Only age stratified by sex (p < 0.05) contributed significantly to the model for LIBRA. Age and presence of hallucinations (p < 0.05) contributed significantly to the model for MoPaRDS. Male sex, older age, excessive daytime sleepiness, and moderate–severe motor symptoms (all p < 0.05) contributed significantly to the model for pPREDICT. CONCLUSION: Although MoPaRDS is a PD-specific tool for predicting cognitive decline relying on only clinical features, it does not focus on potentially modifiable risk factors. LIBRA does focus on potentially modifiable risk factors and is associated with prediction of all-cause dementia in some populations, but pPREDICT potentially demonstrates improved performance in cognitive decline risk calculation in individuals with PD and may identify actionable risk factors. As pPREDICT incorporates multiple potentially modifiable risk factors that can be obtained easily in the clinical setting, it is a first step in developing an easily assessable tool for a personalized approach to reduce dementia risk in people with PD. Frontiers Media S.A. 2023-10-24 /pmc/articles/PMC10628974/ /pubmed/37942138 http://dx.doi.org/10.3389/fnins.2023.1278817 Text en Copyright © 2023 Carlisle, Medina and Holden. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Carlisle, Tara C.
Medina, Luis D.
Holden, Samantha K.
Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease
title Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease
title_full Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease
title_fullStr Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease
title_full_unstemmed Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease
title_short Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease
title_sort original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in parkinson’s disease
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628974/
https://www.ncbi.nlm.nih.gov/pubmed/37942138
http://dx.doi.org/10.3389/fnins.2023.1278817
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