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Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease

BACKGROUND: Cognitive impairment is a common feature of Parkinson's disease (PD). The diagnoses of mild cognitive impairment (MCI) in patients with PD implies an increased risk for later development of dementia, however, it is unclear whether a specific type of cognitive loss confers increased...

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Autores principales: Souza, Carolina Pinto, Oliveira, Guiomar Nascimento, Foss, Maria Paula, Tumas, Vitor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Associação de Neurologia Cognitiva e do Comportamento 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5619271/
https://www.ncbi.nlm.nih.gov/pubmed/29213475
http://dx.doi.org/10.1590/s1980-5764-2016dn1004010
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author Souza, Carolina Pinto
Oliveira, Guiomar Nascimento
Foss, Maria Paula
Tumas, Vitor
author_facet Souza, Carolina Pinto
Oliveira, Guiomar Nascimento
Foss, Maria Paula
Tumas, Vitor
author_sort Souza, Carolina Pinto
collection PubMed
description BACKGROUND: Cognitive impairment is a common feature of Parkinson's disease (PD). The diagnoses of mild cognitive impairment (MCI) in patients with PD implies an increased risk for later development of dementia, however, it is unclear whether a specific type of cognitive loss confers increased risk for faster cognitive decline. OBJECTIVE: Determine whether it was possible to identify distinct cognitive phenotypes in a sample of patients with PD. METHODS: A cross-sectional evaluation of 100 patients with PD recruited from a movement disorders clinic was conducted. The patients were evaluated using the simplified motor score of the UPDRS, the Hoehn and Yahr, Schwab and England, Geriatric Depression Scale, Pfeffer Functional Activities Questionnaire, Clinical Dementia Rating Scale, Mini-Mental State Examination, clock drawing test, digit span, word list battery of CERAD, Frontal Assessment Battery and verbal fluency test. We classified the patients as having normal cognition (PDNC), MCI (PDMCI) or dementia (PDD). Data were analyzed using the chi-square test, non-parametric statistics and cluster analysis. RESULTS: There were 40 patients with PDD, 39 with PDMCI and 21 with PDNC. Patients with PDD were older, had longer disease duration, lower education and lower MMSE scores. Cluster analysis showed 3 general distinct cognitive profiles that represented a continuum from mild to severe impairment of cognition, without distinguishing specific cognitive profiles. CONCLUSION: Cognitive impairment in PD occurs progressively and heterogeneously in most patients. It is unclear whether the definition of the initial phenotype of cognitive loss can be used to establish the cognitive prognosis of patients.
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spelling pubmed-56192712017-12-06 Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease Souza, Carolina Pinto Oliveira, Guiomar Nascimento Foss, Maria Paula Tumas, Vitor Dement Neuropsychol Original Articles BACKGROUND: Cognitive impairment is a common feature of Parkinson's disease (PD). The diagnoses of mild cognitive impairment (MCI) in patients with PD implies an increased risk for later development of dementia, however, it is unclear whether a specific type of cognitive loss confers increased risk for faster cognitive decline. OBJECTIVE: Determine whether it was possible to identify distinct cognitive phenotypes in a sample of patients with PD. METHODS: A cross-sectional evaluation of 100 patients with PD recruited from a movement disorders clinic was conducted. The patients were evaluated using the simplified motor score of the UPDRS, the Hoehn and Yahr, Schwab and England, Geriatric Depression Scale, Pfeffer Functional Activities Questionnaire, Clinical Dementia Rating Scale, Mini-Mental State Examination, clock drawing test, digit span, word list battery of CERAD, Frontal Assessment Battery and verbal fluency test. We classified the patients as having normal cognition (PDNC), MCI (PDMCI) or dementia (PDD). Data were analyzed using the chi-square test, non-parametric statistics and cluster analysis. RESULTS: There were 40 patients with PDD, 39 with PDMCI and 21 with PDNC. Patients with PDD were older, had longer disease duration, lower education and lower MMSE scores. Cluster analysis showed 3 general distinct cognitive profiles that represented a continuum from mild to severe impairment of cognition, without distinguishing specific cognitive profiles. CONCLUSION: Cognitive impairment in PD occurs progressively and heterogeneously in most patients. It is unclear whether the definition of the initial phenotype of cognitive loss can be used to establish the cognitive prognosis of patients. Associação de Neurologia Cognitiva e do Comportamento 2016 /pmc/articles/PMC5619271/ /pubmed/29213475 http://dx.doi.org/10.1590/s1980-5764-2016dn1004010 Text en http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Souza, Carolina Pinto
Oliveira, Guiomar Nascimento
Foss, Maria Paula
Tumas, Vitor
Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease
title Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease
title_full Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease
title_fullStr Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease
title_full_unstemmed Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease
title_short Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease
title_sort cluster analysis of cognitive performance in a sample of patients with parkinson's disease
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5619271/
https://www.ncbi.nlm.nih.gov/pubmed/29213475
http://dx.doi.org/10.1590/s1980-5764-2016dn1004010
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