Delirium Detection Using EEG

Delirium, a prevalent organ dysfunctions in critically ill patients, is independently associated with increased morbidity. This last decade has witnessed an exponential growth in delirium research in hospitalized patients, including those critically ill, and this research has highlighted that delirium needs to be better understood mechanistically, to help foster research that will ultimately lead to its prevention and treatment. In this invited, evidence-based paper, a multinational and interprofessional group of clinicians and researchers from within the fields of critical care medicine, psychiatry, pediatrics, anesthesiology, geriatrics, surgery, neurology, nursing, pharmacy and the neurosciences, sought to address five questions: What is the current standard of care in managing ICU delirium?What have been the major recent advances in delirium research and care?What are the common delirium beliefs that have been challenged by recent trials?What are the remaining areas of uncertainty in delirium research?What are some of the top study areas/trials to be done in the next 10 years? Herein, we briefly review the epidemiology of delirium, the current best practices for management of critically ill patients at risk for delirium or experiencing delirium; identify recent advances in our understanding of delirium as well as gaps in knowledge, and discuss research opportunities and barriers to implementation, with the goal of promoting an integrated research agenda.

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“…A promising approach seems to be a brief EEG registration with a limited number of electrodes and automated processing. [69]…”

Section: What Are Remaining Areas Of Uncertainties/work To Be Done?mentioning

confidence: 99%

The intensive care delirium research agenda: a multinational, interprofessional perspective

et al. 2017

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“…Therefore, in the presence of delirium, the ratios of sleep waves to awake waves (theta waves to alpha waves and delta waves to alpha waves) are significantly higher (Maldonado, 2008). These EEG characteristics have been found to discern patients with delirium from those without delirium while also discriminating delirium from other causes of behavioral change, such as sedation and dementia (van der Kooi et al, 2015). If detected using limited-lead EEG, the sensitivity of these associations would be equal to or better than conventional EEG.…”

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confidence: 96%

“…For example, dopamine levels increase dramatically, while acetylcholine levels drop, resulting in changes in EEG patterns. When the brain's ability to compensate is surpassed, behavioral symptoms begin to appear, meaning delirium is well established before detection (van der Kooi, 2014;van der Kooi et al, 2015). Other neurotransmitters, such as GABA, serotonin, norepinephrine, and glutamate, also begin to change, resulting in the subtypes we know as hyperactive, hypoactive, and mixed delirium (Numan et al, 2017).…”

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confidence: 99%

“…EEG has been validated as an accurate and reliable method to assess for delirium (Plaschke et al, 2010;van der Kooi, 2014;van der Kooi et al, 2015). This method of monitoring is objective, physiological, and capable of early detection.…”

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confidence: 99%

“…Because these devices are capable of using algorithms (EEG waveform modeling solutions that are either associated with or predictive of dependent variables) to assess level of consciousness, researchers and clinicians have determined that use of limited-lead processed EEG may also enable early delirium detection (van der Kooi, Leijten, van der Wekken, & Slooter, 2012;van der Kooi et al, 2015). If an EEG waveform modeling algorithm was developed for the device to detect delirium, limited-lead processed EEG would provide a reliable noninvasive biomarker for delirium (Plaschke et al, 2010).…”

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confidence: 99%

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Methods of identifying delirium: A research protocol

Mulkey

Hardin

Munro

et al. 2019

Research in Nursing & Health

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Delirium is an acute disorder affecting up to 80% of intensive care unit (ICU) patients. It is associated with a 10‐fold increase in cognitive impairment, triples the rate of in‐hospital mortality, and costs $164 billion annually. Delirium acutely affects attention and global cognitive function with fluctuating symptoms caused by underlying organic etiologies. Early detection is crucial because the longer a patient experiences delirium the worse it becomes and the harder it is to treat. Currently, identification is through intermittent clinical assessment using standardized tools, like the Confusion Assessment Method for ICU. Such tools work well in clinical research but do not translate well into clinical practice because they are subjective, intermittent and have low sensitivity. As such, healthcare providers using these tools fail to recognize delirium symptoms as much as 80% of the time. Delirium‐related biochemical derangement leads to electrical changes in electroencephalographic (EEG) patterns followed by behavioral signs and symptoms. However, continuous EEG monitoring is not feasible due to cost and need for skilled interpretation. Studies using limited‐lead EEG show large differences between patients with and without delirium while discriminating delirium from other causes. The Ceribell is a limited‐lead device that analyzes EEG. If it is capable of detecting delirium, it would provide an objective physiological monitor to identify delirium before symptom onset. This pilot study was designed to explore relationships between Ceribell and delirium status. Completion of this study will provide a foundation for further research regarding delirium status using the Ceribell data.

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Effect of Tropisetron on Prevention of Emergence Delirium in Patients After Noncardiac Surgery

et al. 2020

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IMPORTANCE Postoperative delirium is a frequent disorder for patients undergoing surgery and is associated with poor outcomes. Delirium may occur in the immediate period after anesthesia administration and surgery. Tropisetron, which is frequently administrated for postoperative nausea and vomiting, is also a partial agonist of α7 nicotinic acetylcholine receptors associated with neuroprotective effects. Tropisetron may be the potential pharmacological treatment to decrease delirium after noncardiac surgery. OBJECTIVE To perform a randomized clinical trial to determine the efficacy and safety of tropisetron for prevention of emergence delirium in patients undergoing noncardiac surgery. DESIGN, SETTING, AND PARTICIPANTS This single-center, 2-arm randomized, double-blind, placebo-controlled trial will include 1508 patients undergoing noncardiac surgery. The intervention group will receive 5 mg of intravenous tropisetron before anesthesia induction, and patients in the control group will receive a placebo. The primary end point is the incidence of emergence delirium within 1 hour after tracheal tube removal, measured by the Confusion Assessment Method for the Intensive Care Unit score. The main secondary outcome is the incidence of postoperative delirium measured at 3 days of follow-up. An intention-to-treat principle will be used for all analyses. DISCUSSION Delirium remains the most common neuropsychiatric complication for patients after surgery. This will be the first randomized clinical study to evaluate whether tropisetron is effective in preventing emergence delirium. Results from this study will provide evidence for alteration of daily practice. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT04027751

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Delirium Detection Using EEG

Cited by 112 publications

References 30 publications

The intensive care delirium research agenda: a multinational, interprofessional perspective

The intensive care delirium research agenda: a multinational, interprofessional perspective

Methods of identifying delirium: A research protocol

Effect of Tropisetron on Prevention of Emergence Delirium in Patients After Noncardiac Surgery

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