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fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study

Delirium, the clinical expression of acute encephalopathy, is a common neuropsychiatric syndrome that is related to poor outcomes, such as long-term cognitive impairment. Disturbances of functional brain networks are hypothesized to predispose for delirium. The aim of this study in non-delirious eld...

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Autores principales: van Montfort, S.J.T., Slooter, A.J.C., Kant, I.M.J., van der Leur, R.R., Spies, C., de Bresser, J., Witkamp, T.D., Hendrikse, J., van Dellen, E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394743/
https://www.ncbi.nlm.nih.gov/pubmed/32738752
http://dx.doi.org/10.1016/j.nicl.2020.102347
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author van Montfort, S.J.T.
Slooter, A.J.C.
Kant, I.M.J.
van der Leur, R.R.
Spies, C.
de Bresser, J.
Witkamp, T.D.
Hendrikse, J.
van Dellen, E.
author_facet van Montfort, S.J.T.
Slooter, A.J.C.
Kant, I.M.J.
van der Leur, R.R.
Spies, C.
de Bresser, J.
Witkamp, T.D.
Hendrikse, J.
van Dellen, E.
author_sort van Montfort, S.J.T.
collection PubMed
description Delirium, the clinical expression of acute encephalopathy, is a common neuropsychiatric syndrome that is related to poor outcomes, such as long-term cognitive impairment. Disturbances of functional brain networks are hypothesized to predispose for delirium. The aim of this study in non-delirious elderly individuals was to investigate whether predisposing risk factors for delirium are associated with fMRI network characteristics that have been observed during delirium. As predisposing risk factors, we studied age, alcohol misuse, cognitive impairment, depression, functional impairment, history of transient ischemic attack or stroke, and physical status. In this multicenter study, we included 554 subjects and analyzed resting-state fMRI data from 222 elderly subjects (63% male, age range: 65–85 year) after rigorous motion correction. Functional network characteristics were analyzed and based on the minimum spanning tree (MST). Global functional connectivity strength, network efficiency (MST diameter) and network integration (MST leaf fraction) were analyzed, as these measures were altered during delirium in previous studies. Linear regression analyses were used to investigate the relation between predisposing delirium risk factors and delirium-related fMRI characteristics, adjusted for confounding and multiple testing. Predisposing risk factors for delirium were not associated with delirium-related fMRI network characteristics. Older age within our elderly cohort was related to global functional connectivity strength (β = 0.182, p < 0.05), but in the opposite direction than hypothesized. Delirium-related functional network impairments can therefore not be considered as the common mechanism for predisposition for delirium.
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spelling pubmed-73947432020-08-06 fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study van Montfort, S.J.T. Slooter, A.J.C. Kant, I.M.J. van der Leur, R.R. Spies, C. de Bresser, J. Witkamp, T.D. Hendrikse, J. van Dellen, E. Neuroimage Clin Regular Article Delirium, the clinical expression of acute encephalopathy, is a common neuropsychiatric syndrome that is related to poor outcomes, such as long-term cognitive impairment. Disturbances of functional brain networks are hypothesized to predispose for delirium. The aim of this study in non-delirious elderly individuals was to investigate whether predisposing risk factors for delirium are associated with fMRI network characteristics that have been observed during delirium. As predisposing risk factors, we studied age, alcohol misuse, cognitive impairment, depression, functional impairment, history of transient ischemic attack or stroke, and physical status. In this multicenter study, we included 554 subjects and analyzed resting-state fMRI data from 222 elderly subjects (63% male, age range: 65–85 year) after rigorous motion correction. Functional network characteristics were analyzed and based on the minimum spanning tree (MST). Global functional connectivity strength, network efficiency (MST diameter) and network integration (MST leaf fraction) were analyzed, as these measures were altered during delirium in previous studies. Linear regression analyses were used to investigate the relation between predisposing delirium risk factors and delirium-related fMRI characteristics, adjusted for confounding and multiple testing. Predisposing risk factors for delirium were not associated with delirium-related fMRI network characteristics. Older age within our elderly cohort was related to global functional connectivity strength (β = 0.182, p < 0.05), but in the opposite direction than hypothesized. Delirium-related functional network impairments can therefore not be considered as the common mechanism for predisposition for delirium. Elsevier 2020-07-15 /pmc/articles/PMC7394743/ /pubmed/32738752 http://dx.doi.org/10.1016/j.nicl.2020.102347 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Regular Article
van Montfort, S.J.T.
Slooter, A.J.C.
Kant, I.M.J.
van der Leur, R.R.
Spies, C.
de Bresser, J.
Witkamp, T.D.
Hendrikse, J.
van Dellen, E.
fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study
title fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study
title_full fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study
title_fullStr fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study
title_full_unstemmed fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study
title_short fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study
title_sort fmri network correlates of predisposing risk factors for delirium: a cross-sectional study
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394743/
https://www.ncbi.nlm.nih.gov/pubmed/32738752
http://dx.doi.org/10.1016/j.nicl.2020.102347
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