EEG and clinical assessment in delirium and acute encephalopathy

An Interdisciplinary Reappraisal of Delirium and Proposed Subtypes

An interdisciplinary plenary session entitled "Rethinking and Rehashing Delirium" was held during the 2021 Annual Meeting of the Academy of Consultation-Liaison Psychiatry to facilitate dialog on the prevalent approach to delirium. Panel members included a psychiatrist, neurointensivist, and critical care specialist, and attendee comments were solicited with the goal of developing a statement. Discussion was focused on a reappraisal of delirium and, in particular, its disparate terminology and history in relation to acute encephalopathy. The authors endorse a recent joint position statement that describes acute encephalopathy as a rapidly evolving (<4 weeks) pathobiological brain process that presents as subsyndromal delirium, delirium, or coma and suggest the following points of refinement: (1) to suggest that "delirium disorder" describe the diagnostic construct including its syndrome, precipitant(s), and unique pathophysiology; (2) to restrict the term "delirium" to describing the clinical syndrome encountered at the bedside; (3) to clarify that the disfavored term "altered mental status" may occasionally be an appropriate preliminary designation where the diagnosis cannot yet be specified further; and (4) to provide rationale for rejecting the terms acute brain injury, failure, or dysfunction. The final common pathway of delirium appears to involve higher-level brain network dysfunction, but there are many insults that can disrupt functional connectivity. We propose that future delirium classification systems should seek to characterize the unique pathophysiological disturbances ("endotypes") that underlie delirium and delirium's individual neuropsychiatric symptoms. We provide provisional means of classification in hopes that novel subtypes might lead to specific intervention to improve patient experience and outcomes. This paper concludes by considering future directions for the field. Key areas of opportunity include interdisciplinary initiatives to harmonize efforts across specialties and settings, enhance underrepresented groups in research, integration of delirium and encephalopathy in coding, development of relevant quality and safety measures, and exploration of opportunities for translational science.

EEG background frequency is associated with discharge outcomes in non-ICU hospitalized patients with COVID-19

Objective

To assess risk factors for encephalopathy in non-ICU hospitalized patients with COVID-19 and the effect of encephalopathy on short-term outcomes.

Methods

We collected clinical and electrophysiological characteristics of fifty patients with COVID-19 infection admitted to a ward service and who had an electroencephalogram (EEG) performed. Associations with short-term outcomes including hospital length of stay and discharge disposition were determined from univariate and multivariate statistical analysis.

Results

Clinical delirium was associated with encephalopathy on EEG, cefepime use was associated with increased length of stay, and of all factors analyzed, background frequency on EEG alone was correlated with discharge disposition.

Conclusion

Encephalopathy is one of the major determinants of short-term outcomes in hospitalized non-ICU patients with COVID-19.

Comparison Between Deltascan Single Channel Electroencephalography (EEG), Confusion Assessment Method-Intensive Care Unit (CAM-ICU) Score and Clinical Assessment in Diagnosing Delirium in Intubated Patients in the Intensive Care Unit

Background

The aim of this article is to assess the feasibility of using single-channel electroencephalography (EEG) measurement for detecting delirium in intubated Intensive care (ICU) patients and to assess the level of agreement between the EEG measurements, the CAM-ICU score and the clinical diagnosis of delirium.

Materials and methods

This study was an exploratory pilot between May 2021 and September 2021 including intubated patients in the ICU. For this study the Prolira^® (Arnhem, The Netherlands) Deltascan single-channel EEG was used and compared with the Confusion Assessment Method (CAM)-ICU and the clinical diagnosis of delirium by ICU physicians.

Results

In total 23 patients were found eligible for this study, of which 20 were included in the final analysis. The patients mean age was 63.0 ± 8.8 years, and the majority (thirteen) was male (65%). In total 17 of the 20 patients (85%) received the diagnosis delirium by the medical team. There were no statistically significant differences between the Deltascan and CAM-ICU measurements in diagnosing delirium per time point (p values respectively 0.21; 0.90; 0.34; 0.11; 0.056 and 0.091). AUCs for the agreement between the CAM-ICU and the Deltascan measurements were respectively: 0.676 ± 0.205; 0.333 ± 0.224; 0.402 ± 0.146; 0.488 ± 0.202; 0.06 ± 0.077 and 0.06 ± 0.109 (all p>0.05). AUCs for the level of agreement between the clinical diagnosis delirium and Deltascan were: 0.676 ± 0.152; 0.686 ± 0.146; 0.711 ± 0.132; 0.688 ± 0.136; 0.500 ± 0.158 and 0.700 ± 0.211 (all p>0.05).

Conclusion

In this exploratory study, we showed that there is no statistical agreement between CAM-ICU and Delta scan measurements. Secondly, there is a higher agreement, although not statistically significant between the clinical diagnoses of a delirium (by a clinician) with the Deltascan measurements. Despite this small study we think that the Deltascan can be of additional value in intubated ICU patients and therefore larger studies are needed to substantiate our findings.

Using Electroencephalogram Biosignal Changes for Delirium Detection in Intensive Care Units

ABSTRACT

BACKGROUND: Biosignal data acquired during quantitative electroencephalography (QEEG) research may ultimately be used to develop algorithms for more accurate detection of delirium. This study investigates the biosignal changes during delirium states by using the QEEG data of patients in a medical intensive care unit. METHODS: This observational study was conducted between September 2018 and December 2019 at a tertiary hospital in South Korea. Delirium was measured using the Korean version of Confusion Assessment Method for the Intensive Care Unit in intensive care unit patients. Quantitative EEG measurements were recorded for 20 minutes in a natural state without external treatment or stimuli, and QEEG data measured in the centroparietal and parietal regions with eyes open were selected for analysis. Power spectrum analysis with a 5-minute epoch was conducted on the selected 65 cases. RESULTS: QEEG changes in the presence of delirium indicated that alpha, beta, gamma, and spectral edge frequency 50% waves showed significantly lower absolute power spectra than the corresponding findings in the absence of delirium. Brain-mapping results showed that these brain waves were inactivated in delirious states. CONCLUSION: QEEG assessments can potentially detect the changes in the centroparietal and parietal regions of delirium patients. QEEG changes, including lower power spectra of alpha, beta, and gamma waves, and spectral edge frequency 50%, can be successfully used to distinguish delirium from the absence of delirium.

VE-CAM-S: Visual EEG-Based Grading of Delirium Severity and Associations With Clinical Outcomes

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To develop a physiologic grading system for the severity of acute encephalopathy manifesting as delirium or coma, based on EEG, and to investigate its association with clinical outcomes.