Brain network disintegration as a final common pathway for delirium: a systematic review and qualitative meta-analysis

Abstract

Delirium is an acute neuropsychiatric syndrome characterized by altered levels of attention and awareness with cognitive deficits. It is most prevalent in elderly hospitalized patients and related to poor outcomes. Predisposing risk factors, such as older age, determine the baseline vulnerability for delirium, while precipitating factors, such as use of sedatives, trigger the syndrome. Risk factors are heterogeneous and the underlying biological mechanisms leading to vulnerability for delirium are poorly understood. We tested the hypothesis that delirium and its risk factors are associated with consistent brain network changes. We performed a systematic review and qualitative meta-analysis and included 126 brain network publications on delirium and its risk factors. Findings were evaluated after an assessment of methodological quality, providing N=99 studies of good or excellent quality on predisposing risk factors, N=10 on precipitation risk factors and N=7 on delirium. Delirium was consistently associated with functional network disruptions, including lower EEG connectivity strength and decreased fMRI network integration. Risk factors for delirium were associated with lower structural connectivity strength and less efficient structural network organization. Decreased connectivity strength and efficiency appear to characterize structural brain networks of patients at risk for delirium, possibly impairing the functional network, while functional network disintegration seems to be a final common pathway for the syndrome.

Delirium

“…Regardless of primary aetiology, it is hypothesized that impaired neuronal network connectivity may be the final driver of the delirium syndrome; that is, underlying predispositions and superimposed stressors might combine to cause a failure of functional connectivity in neural networks, leading to a profound failure of normal brain function 189 . Brain networks can be studied by analysing statistical relationships between time series of neural activity recorded from different brain areas using functional MRI (fMRI) or EEG 190 .…”

Association of Plasma Neurofilament Light with Postoperative Delirium

“…a Significant at p < 0.05. that older persons, particularly those with underlying cognitive impairment 2,37 or neuroimaging markers of neurodegeneration, 38 have a higher predisposing risk for developing delirium. A recent meta-analysis of 126 studies examining functional neuroimaging and electroencephalographic studies identified that strength and efficiency of connectivity appear to characterize structural brain networks of patients at risk for delirium, 39 supporting the notion that underlying structural brain vulnerability is a key factor for delirium occurrence. Although patients with dementia were excluded from participation, 11% of the patients in the SAGES cohort had mild cognitive impairment by clinical consensus diagnosis at baseline, 40 and we assume, given the age of the cohort, that additional individuals likely have subtle cognitive impairment as well.…”

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

“…Etiological models on delirium have shown a range of relative risk values of predisposing risk factors for delirium (relative risk scores of dementia: 2.3–4.7; cognitive impairment: 1.3–4.2; history of delirium: 3, functional impairment 2.5–4.0; visual impairment: 1.1–3.5; hearing impairment: 1.3; severity of illness or physical status: 1.1–5.6; depression: 1.2–3.2; history of transient ischemic attack or stroke: 1.6; alcohol misuse: 1.4–5.7; older age: 1.1–6.6) ( Inouye et al, 2014 ). Relative risk values or etiological fractions of predisposing risk factors are difficult to quantify as they probably consist of an interaction between predisposition and precipitating events (which may even be non-linear) ( van Montfort et al, 2019 ).…”

“…It has been hypothesized that delirium is a disconnection syndrome, caused by the breakdown of functional brain networks ( Sanders, 2011 , van Dellen et al, 2014 , van Montfort et al, 2019 , Young, 2017 ). The functional network may represent the communication between different brain regions ( Bassett and Sporns, 2017 ).…”