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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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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. |
format | Online Article Text |
id | pubmed-7762505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
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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