Cerebral metabolic covariance in delirium: pattern response to symptomatic changes
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND Delirium is an acute neuropsychiatric condition linked to increased dementia risk, yet its mechanisms remain unclear. Previous studies reported cerebral hypometabolism. Spatial covariance of 18 F‐fluorodeoxyglucose (FDG) positron emission tomography (PET) was applied to acutely unwell inpatients with and without delirium (Delirium, Con unwell ) to derive a delirium‐specific metabolic pattern (DP). DP expression was evaluated in healthy older adults (Con healthy ) and patients with delirium superimposed on dementia (DSD) and tracked longitudinally with symptom resolution. METHODS Seventy participants were included (30 Con healthy , 10 Con unwell, 13 Delirium, 17 DSD). Voxel principal components (PCs) identified intercorrelated metabolic patterns. RESULTS The DP distinguished Con unwell from Delirium, with relative hypometabolism in default, frontoparietal, visual, and frontostriatal networks, and relative hypermetabolism in sensorimotor and limbic hubs. Delirium and DSD demonstrated higher DP expression than controls. In participants with follow‐up, recovery was paralleled by reduced DP expression. DISCUSSION Delirium exhibited a metabolic profile of network dysfunction that may be modifiable and clinically responsive. Highlights Derivation of a DP, primarily attributable to delirium itself, rather than acute illness or dementia. The DP revealed metabolic dysfunction spanning large‐scale networks, consistent with the proposed model of delirium as global brain failure. DP expression was elevated in delirium, both with and without dementia, compared to healthy and acutely unwell controls. In participants with follow‐up, clinical recovery was paralleled by a reduction in DP expression. The delirium pattern reflected clinically responsive and modifiable network dysfunction.
Source: Alzheimer s & Dementia
DOI: 10.1002/alz.70993
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,200
OpenAlex ID: W4417353577
