ArticleNeuroImage. Clinical2020
fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study.
Article in NeuroImage. Clinical, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 17 citations in OpenAlex.
- Dysfunctional resting state network connectivity predicts postoperative delirium after major surgery.British journal of anaesthesia · 2026Article
- Preoperative Cholinergic Signatures Drive Segregated Brain Architecture in Postoperative Delirium.Research square · 2025Article
- Impact of Anesthesia on Brain Functional Networks in Moyamoya Disease and Spinal Lesions.CNS neuroscience & therapeutics · 2025Article
- The Relationship between Delirium and Dementia.Seminars in neurology · 2024Review
- Classifying Unconscious, Psychedelic, and Neuropsychiatric Brain States with Functional Connectivity, Graph Theory, and Cortical Gradient Analysis.Brain sciences · 2024Article
- Correspondence on "Recognition and Management of Delirium in the Neonatal Intensive Care Unit: Case Series From a Single-Center Level IV Intensive Care Unit".Journal of child neurology · 2024Article
- Mechanisms underlying delirium in patients with critical illness.Frontiers in aging neuroscience · 2024Review
- Prediction of the development of delirium after transcatheter aortic valve implantation using preoperative brain perfusion SPECT.PloS one · 2022Article
- Why is delirium more frequent in the elderly?Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021Article
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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