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 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 (ß = 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.

Predisposition for delirium and EEG characteristics.

OBJECTIVE: Delirium is associated with increased electroencephalography (EEG) delta activity, decreased connectivity strength and decreased network integration. To improve our understanding of development of delirium, we studied whether non-delirious individuals with a predisposition for delirium also show these EEG abnormalities. METHODS: Elderly subjects (N = 206) underwent resting-state EEG measurements and were assessed on predisposing delirium risk factors, i.e. older age, alcohol misuse, cognitive impairment, depression, functional impairment, history of stroke and physical status. Delirium-related EEG characteristics of interest were relative delta power, alpha connectivity strength (phase lag index) and network integration (minimum spanning tree leaf fraction). Linear regression analyses were used to investigate the relation between predisposing delirium risk factors and EEG characteristics that are associated with delirium, adjusting for confounding and multiple testing. RESULTS: Functional impairment was related to a decrease in connectivity strength (adjusted R2 = 0.071, ß = 0.201, p < 0.05). None of the other risk factors had significant influence on EEG delta power, connectivity strength or network integration. CONCLUSIONS: Functional impairment seems to be associated with decreased alpha connectivity strength. Other predisposing risk factors for delirium had no effect on the studied EEG characteristics. SIGNIFICANCE: Predisposition for delirium is not consistently related to EEG characteristics that can be found during delirium.

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

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.

Personalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project.

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation.