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Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment

Dementia is a progressive cognitive syndrome, with few effective pharmacological treatments that can slow its progress. Hence, non-pharmacological treatments (NPTs) play an important role in improving patient symptoms and quality of life. Designing the optimal personalised NPT strategy relies on obj...

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Autores principales: Shigihara, Yoshihito, Hoshi, Hideyuki, Poza, Jesús, Rodríguez-González, Víctor, Gómez, Carlos, Kanzawa, Takao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762505/
https://www.ncbi.nlm.nih.gov/pubmed/33289701
http://dx.doi.org/10.18632/aging.202270
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author Shigihara, Yoshihito
Hoshi, Hideyuki
Poza, Jesús
Rodríguez-González, Víctor
Gómez, Carlos
Kanzawa, Takao
author_facet Shigihara, Yoshihito
Hoshi, Hideyuki
Poza, Jesús
Rodríguez-González, Víctor
Gómez, Carlos
Kanzawa, Takao
author_sort Shigihara, Yoshihito
collection PubMed
description Dementia is a progressive cognitive syndrome, with few effective pharmacological treatments that can slow its progress. Hence, non-pharmacological treatments (NPTs) play an important role in improving patient symptoms and quality of life. Designing the optimal personalised NPT strategy relies on objectively and quantitatively predicting the treatment outcome. Magnetoencephalography (MEG) findings can reflect the cognitive status of patients with dementia, and thus potentially predict NPT outcome. In the present study, 16 participants with cognitive impairment underwent NPT for several months. Their cognitive performance was evaluated based on the Mini-Mental State Examination and the Alzheimer's Disease Assessment Scale - Cognitive at the beginning and end of the NPT period, while resting-state brain activity was evaluated using MEG during the NPT period. Our results showed that the spectral properties of MEG signals predicted the changes in cognitive performance scores. High frequency oscillatory intensity at the right superior frontal gyrus medial segment, opercular part of the inferior frontal gyrus, triangular part of the inferior frontal gyrus, post central gyrus, and angular gyrus predicted the changes in cognitive performance scores. Thus, resting-state brain activity may be a powerful tool in designing personalised NPT.
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spelling pubmed-77625052021-01-08 Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment Shigihara, Yoshihito Hoshi, Hideyuki Poza, Jesús Rodríguez-González, Víctor Gómez, Carlos Kanzawa, Takao Aging (Albany NY) Research Paper Dementia is a progressive cognitive syndrome, with few effective pharmacological treatments that can slow its progress. Hence, non-pharmacological treatments (NPTs) play an important role in improving patient symptoms and quality of life. Designing the optimal personalised NPT strategy relies on objectively and quantitatively predicting the treatment outcome. Magnetoencephalography (MEG) findings can reflect the cognitive status of patients with dementia, and thus potentially predict NPT outcome. In the present study, 16 participants with cognitive impairment underwent NPT for several months. Their cognitive performance was evaluated based on the Mini-Mental State Examination and the Alzheimer's Disease Assessment Scale - Cognitive at the beginning and end of the NPT period, while resting-state brain activity was evaluated using MEG during the NPT period. Our results showed that the spectral properties of MEG signals predicted the changes in cognitive performance scores. High frequency oscillatory intensity at the right superior frontal gyrus medial segment, opercular part of the inferior frontal gyrus, triangular part of the inferior frontal gyrus, post central gyrus, and angular gyrus predicted the changes in cognitive performance scores. Thus, resting-state brain activity may be a powerful tool in designing personalised NPT. Impact Journals 2020-12-07 /pmc/articles/PMC7762505/ /pubmed/33289701 http://dx.doi.org/10.18632/aging.202270 Text en Copyright: © 2020 Shigihara et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Shigihara, Yoshihito
Hoshi, Hideyuki
Poza, Jesús
Rodríguez-González, Víctor
Gómez, Carlos
Kanzawa, Takao
Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
title Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
title_full Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
title_fullStr Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
title_full_unstemmed Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
title_short Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
title_sort predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762505/
https://www.ncbi.nlm.nih.gov/pubmed/33289701
http://dx.doi.org/10.18632/aging.202270
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