Delirium detection using relative delta power based on 1-minute single-channel EEG: a multicentre study

DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study

OBJECTIVES

To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs).

DESIGN

Prospective cross-sectional study.

SETTING

Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals.

PARTICIPANTS

494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious.

MEASUREMENTS

DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets.

METHODS

Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus.

RESULTS

DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity.

CONCLUSIONS

DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.

Electroencephalographic Measures of Delirium in the Perioperative Setting: A Systematic Review

Postoperative delirium (POD) is frequent in older adults and is associated with adverse cognitive and functional outcomes. In the last several decades, there has been an increased interest in exploring tools that easily allow the early recognition of patients at risk of developing POD. The electroencephalogram (EEG) is a widely available tool used to understand delirium pathophysiology, and its use in the perioperative setting has grown exponentially, particularly to predict and detect POD. We performed a systematic review to investigate the use of EEG in the pre-, intra-, and postoperative settings. We identified 371 studies, and 56 met the inclusion criteria. A range of techniques was used to obtain EEG data, from limited 1-4 channel setups to complex 256-channel systems. Power spectra were often measured preoperatively, yet the outcomes were inconsistent. During surgery, the emphasis was primarily on burst suppression (BS) metrics and power spectra, with a link between the frequency and timing of BS, and POD. The EEG patterns observed in POD aligned with those noted in delirium in different contexts, suggesting a reduction in EEG activity. Further research is required to investigate preoperative EEG indicators that may predict susceptibility to delirium.

Electroencephalographic insights into the pathophysiological mechanisms of emergence delirium in children and corresponding clinical treatment strategies

Emergence delirium is a common postoperative complication in patients undergoing general anesthesia, especially in children. In severe cases, it can cause unnecessary self-harm, affect postoperative recovery, lead to parental dissatisfaction, and increase medical costs. With the widespread use of inhalation anesthetic drugs (such as sevoflurane and desflurane), the incidence of emergence delirium in children is gradually increasing; however, its pathogenesis in children is complex and unclear. Several studies have shown that age, pain, and anesthetic drugs are strongly associated with the occurrence of emergence delirium. Alterations in central neurophysiology are essential intermediate processes in the development of emergence delirium. Compared to adults, the pediatric nervous system is not fully developed; therefore, the pediatric electroencephalogram may vary slightly by age. Moreover, pain and anesthetic drugs can cause changes in the excitability of the central nervous system, resulting in electroencephalographic changes. In this paper, we review the pathogenesis of and prevention strategies for emergence delirium in children from the perspective of brain electrophysiology-especially for commonly used pharmacological treatments-to provide the basis for understanding the development of emergence delirium as well as its prevention and treatment, and to suggest future research direction.

Effect of Atypical Sleep EEG Patterns on Weaning From Prolonged Mechanical Ventilation

BACKGROUND

Approximately one-third of acute ICU patients display atypical sleep patterns that cannot be interpreted by using standard EEG criteria for sleep. Atypical sleep patterns have been associated with poor weaning outcomes in acute ICUs.

RESEARCH QUESTION

Do patients being weaned from prolonged mechanical ventilation experience atypical sleep EEG patterns, and are these patterns linked with weaning outcomes?

STUDY DESIGN AND METHODS

EEG power spectral analysis during wakefulness and overnight polysomnogram were performed on alert, nondelirious patients at a long-term acute care facility.

RESULTS

Forty-four patients had been ventilated for a median duration of 38 days at the time of the polysomnogram study. Eleven patients (25%) exhibited atypical sleep EEG. During wakefulness, relative EEG power spectral analysis revealed higher relative delta power in patients with atypical sleep than in patients with usual sleep (53% vs 41%; P < .001) and a higher slow-to-fast power ratio during wakefulness: 4.39 vs 2.17 (P < .001). Patients with atypical sleep displayed more subsyndromal delirium (36% vs 6%; P = .027) and less rapid eye movement sleep (4% vs 11% total sleep time; P < .02). Weaning failure was more common in the atypical sleep group than in the usual sleep group: 91% vs 45% (P = .013).

INTERPRETATION

This study provides the first evidence that patients in a long-term acute care facility being weaned from prolonged ventilation exhibit atypical sleep EEG patterns that are associated with weaning failure. Patients with atypical sleep EEG patterns had higher rates of subsyndromal delirium and slowing of the wakeful EEG, suggesting that these two findings represent a biological signal for brain dysfunction.

Delirium and delirium severity screening in the intensive care-correspondence of screenings tools

BACKGROUND

Delirium severity scores are gaining acceptance for measuring delirium in the intensive care unit (ICU).

OBJECTIVE

The aim of this study was to evaluate the concordance between the Confusion Assessment Method for the intensive care unit (CAM-ICU)-7 and the Intensive Care Delirium Screening Checklist (ICDSC) as delirium severity measurement tools.

METHODS

This was a prospective, comparative, observational multicentre study. This study was conducted in 18 Danish ICUs. Delirium was assessed in adult critically ill patients admitted to an ICU with a Richmond Agitation and Sedation Score (RASS) of -2 or above. ICU nurses assessed delirium with randomised paired delirium screening instruments, using the CAM-ICU, the ICDSC, and the CAM-ICU-7. The correlation between the CAM-ICU-7 and the ICDSC severity scores was evaluated for all predefined patient subgroups.

RESULTS

A total of 1126 paired screenings were conducted by 127 ICU nurses in 850 patients. The patients' median age was 70 years (interquartile range: 61-77), 40% (339/850) were female, and 54% (457/850) had at least one positive delirium score. Delirium severity ranges (CAM-ICU-7: 0-7; and ICDSC: 0-8) were positively correlated (Pearson's correlation coefficient, r = 0.83; p < 0.0001). The overall agreement between the CAM-ICU-7 and the ICDSC for delirium measurement (CAM-ICU-7: >2, and ICDSC: >3) was substantial (kappa = 0.74), but the agreement decreased to fair (kappa = 0.38) if a patient had a RASS less than 0.

CONCLUSIONS

The agreement between the CAM-ICU-7 and the ICDSC for delirium severity measurement was substantial but might be affected by the patient's sedation and agitation level at the time of assessment.

IMPLICATIONS FOR PRACTICE

Both CAM-ICU-7 and ICDSC can be implemented for delirium severity measurement. Attention is warranted in both scores if a patient has a RASS of -2.

Single-channel qEEG characteristics distinguish delirium from no delirium, but not postoperative from non-postoperative delirium

OBJECTIVE

This exploratory study examined quantitative electroencephalography (qEEG) changes in delirium and the use of qEEG features to distinguish postoperative from non-postoperative delirium.

METHODS

This project was part of the DeltaStudy, a cross-sectional,multicenterstudy in Intensive Care Units (ICUs) and non-ICU wards. Single-channel (Fp2-Pz) four-minutes resting-state EEG was analyzed in 456 patients. After calculating 98 qEEG features per epoch, random forest (RF) classification was used to analyze qEEG changes in delirium and to test whether postoperative and non-postoperative delirium could be distinguished.

RESULTS

An area under the receiver operatingcharacteristic curve (AUC) of 0.76 (95% Confidence Interval (CI) 0.71-0.80) was found when classifying delirium with a sensitivity of 0.77 and a specificity of 0.63 at the optimal operating point. The classification of postoperative versus non-postoperative delirium resulted in an AUC of 0.50 (95%CI 0.38-0.61).

CONCLUSIONS

RF classification was able to discriminate delirium from no delirium with reasonable accuracy, while also identifying new delirium qEEG markers like autocorrelation and theta peak frequency. RF classification could not distinguish postoperative from non-postoperative delirium.

SIGNIFICANCE

Single-channel EEG differentiates between delirium and no delirium with reasonable accuracy. We found no distinct EEG profile for postoperative delirium, which may suggest that delirium is one entity, whether it develops postoperatively or not.

Relative band power in assessing temporary neurological dysfunction post- type A aortic dissection surgery: a prospective study

Temporary neurological dysfunction (TND), a common complication following surgical repair of Type A Aortic Dissection (TAAD), is closely associated with increased mortality and long-term cognitive impairment. Currently, effective treatment options for TND remain elusive. Therefore, we sought to investigate the potential of postoperative relative band power (RBP) in predicting the occurrence of postoperative TND, with the aim of identifying high-risk patients prior to the onset of TND. We conducted a prospective observational study between February and December 2022, involving 165 patients who underwent surgical repair for TAAD at our institution. Bedside Quantitative electroencephalography (QEEG) was utilized to monitor the post-operative brain electrical activity of each participant, recording changes in RBP (RBP Delta, RBP Theta, RBP Beta and RBP Alpha), and analyzing their correlation with TND. Univariate and multivariate analyses were employed to identify independent risk factors for TND. Subsequently, line graphs were generated to estimate the incidence of TND. The primary outcome of interest was the development of TND, while secondary outcomes included intensive care unit (ICU) admission and length of hospital stay. A total of 165 patients were included in the study, among whom 68 (41.2%) experienced TND. To further investigate the independent risk factors for postoperative TND, we conducted both univariate and multivariate logistic regression analyses on all variables. In the univariate regression analysis, we identified age (Odds Ratio [OR], 1.025; 95% CI, 1.002-1.049), age ≥ 60 years (OR, 2.588; 95% CI, 1.250-5.475), hemopericardium (OR, 2.767; 95% CI, 1.150-7.009), cardiopulmonary bypass (CPB) (OR, 1.007; 95% CI, 1.001-1.014), RBP Delta (OR, 1.047; 95% CI, 1.020-1.077), RBP Alpha (OR, 0.853; 95% CI, 0.794-0.907), and Beta (OR, 0.755; 95% CI, 0.649-0.855) as independent risk factors for postoperative TND. Further multivariate regression analyses, we discovered that CPB time ≥ 180 min (OR, 1.021; 95% CI, 1.011-1.032), RBP Delta (OR, 1.168; 95% CI, 1.105-1.245), and RBP Theta (OR, 1.227; 95% CI, 1.135-1.342) emerged as independent risk factors. TND patients had significantly longer ICU stays (p < 0.001), and hospital stays (p = 0.002). We obtained the simplest predictive model for TND, consisting of three variables (CPB time ≥ 180 min, RBP Delta, RBP Theta, upon which we constructed column charts. The areas under the receiver operating characteristic (AUROC) were 0.821 (0.755, 0.887). Our study demonstrates that postoperative RBP monitoring can detect changes in brain function in patients with TAAD during the perioperative period, providing clinicians with an effective predictive method that can help improve postoperative TND in TAAD patients. These findings have important implications for improving clinical care in this population.Trial registration ChiCTR2200055980. Registered 30th Jan. 2022. This trial was registered before the first participant was enrolled.

Predicting postoperative delirium after cardiovascular surgeries from preoperative portable electroencephalography oscillations

Introduction

Postoperative delirium (POD) is common and life-threatening, however, with intensive interventions, a potentially preventable clinical syndrome. Although electroencephalography (EEG) is a promising biomarker of delirium, standard 20-leads EEG holds difficulties for screening usage in clinical practice.

Objective

We aimed to develop an accurate algorithm to predict POD using EEG data obtained from portable device.

Methods

We recruited 128 patients who underwent scheduled cardiovascular surgery. Cognitive function assessments were conducted, and portable EEG recordings were obtained prior to surgery.

Results

Among the patients, 47 (36.7%) patients with POD were identified and they did not significantly differ from patients without POD in sex ratio, age, cognitive function, or treatment duration of intensive care unit. However, significant differences were observed in the preoperative EEG power spectrum densities at various frequencies, especially gamma activity, between patients with and without POD. POD was successfully predicted using preoperative EEG data with a machine learning algorithm, yielding accuracy of 86% and area under the receiver operating characteristic curve of 0.93.

Discussion

This study provides new insights into the objective and biological vulnerability to delirium. The developed algorithm can be applied in general hospitals without advanced equipment and expertise, thereby enabling the reduction of POD occurrences with intensive interventions for high-risk patients.

Delta power during sleep is modulated by EEG-gated auricular vagal afferent nerve stimulation (EAVANS)

Vagus nerve stimulation (VNS) has many clinical applications under development. In particular, there is a large interest in transcutaneous auricular VNS (taVNS) because it is non-invasive and provides easy access to neuromodulation. The present study proposes a novel approach for electroencephalography (EEG)-gated taVNS, with the ultimate goal of enhancing therapeutic outcomes, including for the treatment of delirium. Delirium arises from an altered state of consciousness and is the most common neuropsychiatric disorder observed in hospitalized patients, especially the elderly. Delirium has been linked to specific disturbances in EEG rhythms. Here, we propose an EEG-gated auricular vagal afferent nerve stimulation (EAVANS) approach to deliver stimulation targeting a specific instantaneous phase of the EEG Delta rhythm to modulate arousal and downstream reduction of neuroinflammation, two of the contributing factors to delirium. We hypothesize that treatment with EAVANS will modulate Delta power, which has been linked with delirium. As dominant Delta power is also a typical feature of non-rapid eye movement (NREM) sleep, we applied a prototype of an EAVANS device on healthy volunteers during sleep to establish preliminary validation. We successfully employed our closed-loop approach to target vagal afference during the rising Delta phase in the range [-π/2 0] radians. We found a significant reduction in Delta wave power for stimulation during the rising Delta phase compared to 1) absence of stimulation, 2) active stimulation during the descending Delta phase, and 3) active stimulation targeting non-vagal territory (i.e. greater auricular nerve) during the rising Delta phase. Further validation of our EEG-gated taVNS approach in the peri-operative period will be needed. As there is presently a lack of effective treatments for delirium, our non-pharmacological and non-invasive approach, if validated, could be easily deployed in clinical settings.Clinical Relevance- Given the serious health consequences and costs associated with delirium, and the absence of effective non-pharmacological treatments, the proposed neuromodulatory approach may be a promising option for reducing delirium and other disorders of consciousness. Our EAVANS prototype system has been tested on healthy volunteers during a NREM sleep state and will require further validation in different patient populations to optimize the proposed technology and gather more evidence to support its clinical utility. This novel non-pharmacological and non-invasive closed-loop neuromodulatory device could be used peri-operatively and in inpatient hospital settings to treat patients at risk of developing delirium. For instance, in a pre-operative setting, this technology may provide an effective preventative "pre-habilitation" approach for patients at high risk of developing delirium. Post-operatively, our technology may help manage patients with delirium more effectively.

A Real-Time Neurophysiologic Stress Test for the Aging Brain: Novel Perioperative and ICU Applications of EEG in Older Surgical Patients

As of 2022, individuals age 65 and older represent approximately 10% of the global population [1], and older adults make up more than one third of anesthesia and surgical cases in developed countries [2, 3]. With approximately > 234 million major surgical procedures performed annually worldwide [4], this suggests that > 70 million surgeries are performed on older adults across the globe each year. The most common postoperative complications seen in these older surgical patients are perioperative neurocognitive disorders including postoperative delirium, which are associated with an increased risk for mortality [5], greater economic burden [6, 7], and greater risk for developing long-term cognitive decline [8] such as Alzheimer's disease and/or related dementias (ADRD). Thus, anesthesia, surgery, and postoperative hospitalization have been viewed as a biological "stress test" for the aging brain, in which postoperative delirium indicates a failed stress test and consequent risk for later cognitive decline (see Fig. 3). Further, it has been hypothesized that interventions that prevent postoperative delirium might reduce the risk of long-term cognitive decline. Recent advances suggest that rather than waiting for the development of postoperative delirium to indicate whether a patient "passed" or "failed" this stress test, the status of the brain can be monitored in real-time via electroencephalography (EEG) in the perioperative period. Beyond the traditional intraoperative use of EEG monitoring for anesthetic titration, perioperative EEG may be a viable tool for identifying waveforms indicative of reduced brain integrity and potential risk for postoperative delirium and long-term cognitive decline. In principle, research incorporating routine perioperative EEG monitoring may provide insight into neuronal patterns of dysfunction associated with risk of postoperative delirium, long-term cognitive decline, or even specific types of aging-related neurodegenerative disease pathology. This research would accelerate our understanding of which waveforms or neuronal patterns necessitate diagnostic workup and intervention in the perioperative period, which could potentially reduce postoperative delirium and/or dementia risk. Thus, here we present recommendations for the use of perioperative EEG as a "predictor" of delirium and perioperative cognitive decline in older surgical patients.

Preclinical and translational models for delirium: Recommendations for future research from the NIDUS delirium network

Delirium is a common, morbid, and costly syndrome that is closely linked to Alzheimer's disease (AD) and AD-related dementias (ADRD) as a risk factor and outcome. Human studies of delirium have advanced our knowledge of delirium incidence and prevalence, risk factors, biomarkers, outcomes, prevention, and management. However, understanding of delirium neurobiology remains limited. Preclinical and translational models for delirium, while challenging to develop, could advance our knowledge of delirium neurobiology and inform the development of new prevention and treatment approaches. We discuss the use of preclinical and translational animal models in delirium, focusing on (1) a review of current animal models, (2) challenges and strategies for replicating elements of human delirium in animals, and (3) the utility of biofluid, neurophysiology, and neuroimaging translational markers in animals. We conclude with recommendations for the development and validation of preclinical and translational models for delirium, with the goal of advancing awareness in this important field.

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.

Cohort profile of PLUTO: a perioperative biobank focusing on prediction and early diagnosis of postoperative complications

PURPOSE

Although elective surgery is generally safe, some procedures remain associated with an increased risk of complications. Improved preoperative risk stratification and earlier recognition of these complications may ameliorate postoperative recovery and improve long-term outcomes. The perioperative longitudinal study of complications and long-term outcomes (PLUTO) cohort aims to establish a comprehensive biorepository that will facilitate research in this field. In this profile paper, we will discuss its design rationale and opportunities for future studies.

PARTICIPANTS

Patients undergoing elective intermediate to high-risk non-cardiac surgery are eligible for enrolment. For the first seven postoperative days, participants are subjected to daily bedside visits by dedicated observers, who adjudicate clinical events and perform non-invasive physiological measurements (including handheld spirometry and single-channel electroencephalography). Blood samples and microbiome specimens are collected at preselected time points. Primary study outcomes are the postoperative occurrence of nosocomial infections, major adverse cardiac events, pulmonary complications, acute kidney injury and delirium/acute encephalopathy. Secondary outcomes include mortality and quality of life, as well as the long-term occurrence of psychopathology, cognitive dysfunction and chronic pain.

FINDINGS TO DATE

Enrolment of the first participant occurred early 2020. During the inception phase of the project (first 2 years), 431 patients were eligible of whom 297 patients consented to participate (69%). Observed event rate was 42% overall, with the most frequent complication being infection.

FUTURE PLANS

The main purpose of the PLUTO biorepository is to provide a framework for research in the field of perioperative medicine and anaesthesiology, by storing high-quality clinical data and biomaterials for future studies. In addition, PLUTO aims to establish a logistical platform for conducting embedded clinical trials.

TRIAL REGISTRATION NUMBER

NCT05331118.

Delirium-related psychiatric and neurocognitive impairment and the association with post-intensive care syndrome-A narrative review

INTRODUCTION

Delirium is common among patients admitted to the intensive care unit (ICU) and its impact on the neurocognitive and psychiatric state of survivors is of great interest. These new-onset or worsening conditions, together with physical alterations, are called post-intensive care syndrome (PICS). Our aim is to update on the latest screening and follow-up options for psychological and cognitive sequelae of PICS.

METHOD

This narrative review discusses the occurrence of delirium in ICU settings and the relatively new concept of PICS. Psychiatric and neurocognitive morbidities that may occur in survivors of critical illness following delirium are addressed. Future perspectives for practice and research are discussed.

RESULTS

There is no "gold standard" for diagnosing delirium in the ICU, but two extensively validated tools, the confusion assessment method for the ICU and the intensive care delirium screening checklist, are often used. PICS complaints are frequent in ICU survivors who have suffered delirium and have been recognized as an important public health and socio-economic problem worldwide. Depression, anxiety, post-traumatic stress disorder, and long-term cognitive impairment are recurrently exhibited. Screening tools for these deficits are discussed, as well as the suggestion of early assessment after discharge and at 3 and 12 months.

CONCLUSIONS

Delirium is a complex but common phenomenon in the ICU and a risk factor for PICS. Its diagnosis is challenging with potential long-term adverse outcomes, including psychiatric and cognitive difficulties. The implementation of screening and follow-up protocols for PICS sequelae is warranted to ensure early detection and appropriate management.

Postoperative Delirium Severity and Recovery Correlate With Electroencephalogram Spectral Features

BACKGROUND

Delirium is an acute syndrome characterized by inattention, disorganized thinking, and an altered level of consciousness. A reliable biomarker for tracking delirium does not exist, but oscillations in the electroencephalogram (EEG) could address this need. We evaluated whether the frequencies of EEG oscillations are associated with delirium onset, severity, and recovery in the postoperative period.

METHODS

Twenty-six adults enrolled in the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES; ClinicalTrials.gov NCT02241655) study underwent major surgery requiring general anesthesia, and provided longitudinal postoperative EEG recordings for this prespecified substudy. The presence and severity of delirium were evaluated with the confusion assessment method (CAM) or the CAM-intensive care unit. EEG data obtained during awake eyes-open and eyes-closed states yielded relative power in the delta (1-4 Hz), theta (4-8 Hz), and alpha (8-13 Hz) bands. Discriminability for delirium presence was evaluated with c-statistics. To account for correlation among repeated measures within patients, mixed-effects models were generated to assess relationships between: (1) delirium severity and EEG relative power (ordinal), and (2) EEG relative power and time (linear). Slopes of ordinal and linear mixed-effects models are reported as the change in delirium severity score/change in EEG relative power, and the change in EEG relative power/time (days), respectively. Bonferroni correction was applied to confidence intervals (CIs) to account for multiple comparisons.

RESULTS

Occipital alpha relative power during eyes-closed states offered moderate discriminability (c-statistic, 0.75; 98% CI, 0.58-0.87), varying inversely with delirium severity (slope, -0.67; 98% CI, -1.36 to -0.01; P = .01) and with severity of inattention (slope, -1.44; 98% CI, -2.30 to -0.58; P = .002). Occipital theta relative power during eyes-open states correlated directly with severity of delirium (slope, 1.28; 98% CI, 0.12-2.44; P = .007), inattention (slope, 2.00; 98% CI, 0.48-3.54; P = .01), and disorganized thinking (slope, 3.15; 98% CI, 0.66-5.65; P = .01). Corresponding frontal EEG measures recapitulated these relationships to varying degrees. Severity of altered level of consciousness correlated with frontal theta relative power during eyes-open states (slope, 11.52; 98% CI, 6.33-16.71; P < .001). Frontal theta relative power during eyes-open states correlated inversely with time (slope, -0.05; 98% CI, -0.12 to -0.04; P = .002).

CONCLUSIONS

Presence, severity, and core features of postoperative delirium covary with spectral features of the EEG. The cost and accessibility of EEG facilitate the translation of these findings to future mechanistic and interventional trials.

Is there evidence for using anticonvulsants in the prevention and/or treatment of delirium among older adults?

OBJECTIVE

This systematic review aims to identify published randomized controlled trials (RCTs) that evaluated the use of anticonvulsants for the prevention and/or treatment of delirium among older adults.

METHODS

A comprehensive search of databases: MEDLINE ALL (Ovid), Embase (Ovid), PsycINFO (Ovid), Web of Science Core Collection and Cochrane Central Register of Controlled was conducted.

RESULTS

The search identified four RCTs that evaluated the use of anticonvulsants among older adults with delirium. One RCT evaluated the perioperative use of gabapentin among individuals undergoing spinal surgery and the development of postoperative delirium. One RCT evaluated the relationship between the use of perioperative gabapentin and the development of postoperative delirium among individuals undergoing spinal surgery and hip and knee arthroplasty. Two post-hoc analyses of RCTs evaluated the use of gabapentin and pregabalin among individuals undergoing total knee arthroplasty (TKA) and total hip arthroplasty (THA). The perioperative use of gabapentin reduced the incidence of postoperative delirium among older adults undergoing spinal surgery. The perioperative use of gabapentin did not reduce the rates, severity or duration of postoperative delirium among older adults who were undergoing spine and hip and knee arthroplasty. The perioperative use of gabapentin did not reduce the incidence or duration of postoperative delirium among older adults undergoing elective TKA. The perioperative use of pregabalin did not reduce the incidence of postoperative delirium among older adults undergoing elective THA. Gabapentin and pregabalin were well tolerated among the individuals enrolled in these trials. There were no RCTs identified that evaluated the use of other anticonvulsants for the prevention and/or treatment of delirium among older adults.

CONCLUSIONS

Based on current evidence, the routine use of anticonvulsants for the prevention and/or treatment of delirium among older adults cannot be recommended.

An Automated Algorithm for Determining Sleep Using Single-Channel Electroencephalography to Detect Delirium: A Prospective Observational Study in Intensive Care Units

The relationship between polysomnography-based objective sleep and delirium in the intensive care unit (ICU) is inconsistent across studies, suggesting limitations in manually determining the sleep stage of critically ill patients. We objectively measured 24-h sleep using a single-channel electroencephalogram (SleepScope [SS]) and an under-mattress sleep monitor (Nemuri SCAN [NSCAN]), both of which have independent algorithms that automatically determine sleep and wakefulness. Eighteen patients (median age, 68 years) admitted to the ICU after valvular surgery or coronary artery bypass grafting were included, and their sleep time was measured one day after extubation. The median total sleep times (TSTs) measured by SS (TST-SS) and NSCAN were 548 (48−1050) and 1024 (462−1257) min, respectively. Two patients with delirium during the 24-h sleep measurement had very short TST-SS of 48 and 125 min, and the percentage of daytime sleep accounted for >80% in both SS and NSCAN. This preliminary case series showed marked sleep deprivation and increased rates of daytime sleeping in ICU patients with delirium. Although data accuracy from under-mattress sleep monitors is contentious, automated algorithmic sleep/wakefulness determination using a single-channel electroencephalogram may be useful in detecting delirium in ICU patients and could even be superior to polysomnography.

Association of electroencephalogram epileptiform discharges during cardiac surgery with postoperative delirium: An observational study

Background

Delirium is a frequent and serious complication following cardiac surgery involving cardiopulmonary bypass (CPB). Electroencephalography reflects the electrical activity of the cerebral cortex. The impact of electroencephalographic epileptiform discharges during cardiac surgery on postoperative delirium remains unclear. This study was designed to investigate the relationship between intraoperative epileptiform discharges and postoperative delirium in patients undergoing cardiac surgery.

Methods

A total of 76 patients who underwent cardiac surgery under CPB were included. The baseline cognitive status was measured before surgery. Electroencephalograms were monitored continuously from entry into the operating room to the end of surgery. The presence of delirium was assessed through the Confusion Assessment Method or the Confusion Assessment Method for the Intensive Care Unit on the first 3 days after surgery. Univariate and multivariate logistic regression analyses were performed to evaluate the association between epileptiform discharges and delirium.

Results

Delirium occurred in 31% of patients and epileptiform discharges were present in 26% of patients in the study. Patients with delirium had a higher incidence of epileptiform discharges (52.63% vs. 13.95%, P &lt; 0.001) and longer durations of anesthesia and CPB (P = 0.023 and P = 0.015, respectively). In addition, patients with delirium had a longer length of hospital stay and a higher incidence of postoperative complications. Multivariate logistic regression analysis showed that age and epileptiform discharges were significantly associated with the incidence of postoperative delirium [odds ratio, 4.75 (1.26–17.92), P = 0.022; 5.00 (1.34–18.74), P = 0.017, respectively].

Conclusions

Postoperative delirium is significantly related to the occurrence of epileptiform discharges during cardiac surgery.

Feasibility and potential of a bedside mini-EEG for diagnosing delirium superimposed on dementia

OBJECTIVE

Delirium superimposed on dementia (DSD) is difficult to diagnose because symptoms of delirium might be interpreted as symptoms of dementia. To improve diagnostic accuracy, we investigated the potential of a brief point-of-care EEG measurement.

METHODS

Thirty older patients were included, all with Major Neurocognitive Disorder (i.e. dementia) according to DSM-5 criteria. EEG was registered at right prefrontal and right temporal site, with eyes either open or closed for three minutes, simultaneously with the Discomfort Scale for Dementia of Alzheimer Type. The Confusion Assessment Method for the Intensive Care Unit was administered to determine the presence of symptoms of a delirium at the time of EEG administration. Video registrations were reviewed independently by two delirium experts.

RESULTS

Higher activities of delta and theta1, and lower activities of theta2, alpha, and beta activity, were found in DSD when compared to dementia only. The ratio of delta and theta power during eyes-open conditions had the highest accuracy (AUC = 0.80 [0.63-0.94]; p <.001) to distinguish DSD from dementia alone. All subjects were on benzodiazepines and half on clozapine, thus the effects of psychotropics on EEG cannot be fully excluded.

CONCLUSIONS

A brief point-of-care EEG at two sites of the head has the potential to aid in the detection of DSD.

SIGNIFICANCE

The diagnostic accuracy of EEG in recognizing or excluding delirium in patients who already have dementia is of large potential given the lack of proper diagnostic tools.

Electroencephalogram Features of Perioperative Neurocognitive Disorders in Elderly Patients: A Narrative Review of the Clinical Literature

Postoperative neurocognitive disorder (PND) is a common postoperative complication, particularly in older patients. Electroencephalogram (EEG) monitoring, a non-invasive technique with a high spatial-temporal resolution, can accurately characterize the dynamic changes in brain function during the perioperative period. Current clinical studies have confirmed that the power density of alpha oscillation during general anesthesia decreased with age, which was considered to be associated with increased susceptibility to PND in the elderly. However, evidence on whether general anesthesia under EEG guidance results in a lower morbidity of PND is still contradictory. This is one of the reasons that common indicators of the depth of anesthesia were limitedly derived from EEG signals in the frontal lobe. The variation of multi-channel EEG features during the perioperative period has the potential to highlight the occult structural and functional abnormalities of the subcortical-cortical neurocircuit. Therefore, we present a review of the application of multi-channel EEG monitoring to predict the incidence of PND in older patients. The data confirmed that the abnormal variation in EEG power and functional connectivity between distant brain regions was closely related to the incidence and long-term poor outcomes of PND in older adults.

At the Crossroads of Minimally Invasive Mitral Valve Surgery—Benching Single Hospital Experience to a National Registry: A Plea for Risk Management Technology

Almost 30 years after the first endoscopic mitral valve repair, Minimally Invasive Mitral Valve Surgery (MIMVS) has become the standard at many institutions due to optimal clinical results and fast recovery. The question that arises is can already good results be further improved by an Institutional Risk Management Performance (IRMP) system in decreasing risks in minimally invasive mitral valve surgery (MIMVS)? As of yet, there are no reports on IRMP and learning systems in the literature. (2) Methods: We described and appraised our five-year single institutional experience with MIMVS in isolated valve surgery included in the Netherlands Heart Registry (NHR) and investigated root causes of high-impact complications. (3) Results: The 120-day and 12-month mortality were 1.1% and 1.9%, respectively, compared to the average of 4.3% and 5.3% reported in the NHR. The regurgitation rate was 1.4% compared to 5.2% nationwide. The few high-impact complications appeared not to be preventable. (4) Discussion: In MIMVS, freedom from major and minor complications is a strong indicator of an effective IRMP but remains concealed from physicians and patients, despite its relevance to shared decision making. Innovation adds to the complexity of MIMVS and challenges surgical competence. An IRMP system may detect and control new risks earlier. (5) Conclusion: An IRMP system contributes to an effective reduction of risks, pain and discomfort; provides relevant input for shared decision making; and warrants the safe introduction of new technology. Crossroads conclusions: investment in machine learning and AI for an effective IRMP system is recommended and the roles for commanding and operating surgeons should be considered.

The future of intensive care: delirium should no longer be an issue

In the ideal intensive care unit (ICU) of the future, all patients are free from delirium, a syndrome of brain dysfunction frequently observed in critical illness and associated with worse ICU-related outcomes and long-term cognitive impairment. Although screening for delirium requires limited time and effort, this devastating disorder remains underestimated during routine ICU care. The COVID-19 pandemic brought a catastrophic reduction in delirium monitoring, prevention, and patient care due to organizational issues, lack of personnel, increased use of benzodiazepines and restricted family visitation. These limitations led to increases in delirium incidence, a situation that should never be repeated. Good sedation practices should be complemented by novel ICU design and connectivity, which will facilitate non-pharmacological sedation, anxiolysis and comfort that can be supplemented by balanced pharmacological interventions when necessary. Improvements in the ICU sound, light control, floor planning, and room arrangement can facilitate a healing environment that minimizes stressors and aids delirium prevention and management. The fundamental prerequisite to realize the delirium-free ICU, is an awake non-sedated, pain-free comfortable patient whose management follows the A to F (A-F) bundle. Moreover, the bundle should be expanded with three additional letters, incorporating humanitarian care: gaining (G) insight into patient needs, delivering holistic care with a 'home-like' (H) environment, and redefining ICU architectural design (I). Above all, the delirium-free world relies upon people, with personal challenges for critical care teams to optimize design, environmental factors, management, time spent with the patient and family and to humanize ICU care.

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.

Quantitative EEG may predict weaning failure in ventilated patients on the neurological intensive care unit

Neurocritical patients suffer from a substantial risk of extubation failure. The aim of this prospective study was to analyze if quantitative EEG (qEEG) monitoring is able to predict successful extubation in these patients. We analyzed EEG-monitoring for at least six hours before extubation in patients receiving mechanical ventilation (MV) on our neurological intensive care unit (NICU) between November 2017 and May 2019. Patients were divided in 2 groups: patients with successful extubation (SE) versus patients with complications after MV withdrawal (failed extubation; FE), including reintubation, need for non-invasive ventilation (NIV) or death. Bipolar six channel EEG was applied. Unselected raw EEG signal underwent automated artefact rejection and Short Time Fast Fourier Transformation. The following relative proportions of global EEG spectrum were analyzed: relative beta (RB), alpha (RA), theta (RT), delta (RD) as well as the alpha delta ratio (ADR). Coefficient of variation (CV) was calculated as a measure of fluctuations in the different power bands. Mann-Whitney U test and logistic regression were applied to analyze group differences. 52 patients were included (26 male, mean age 65 ± 17 years, diagnosis: 40% seizures/status epilepticus, 37% ischemia, 13% intracranial hemorrhage, 10% others). Successful extubation was possible in 40 patients (77%), reintubation was necessary in 6 patients (12%), 5 patients (10%) required NIV, one patient died. In contrast to FE patients, SE patients showed more stable EEG power values (lower CV) considering all EEG channels (RB: p < 0.0005; RA: p = 0.045; RT: p = 0.045) with RB as an independent predictor of weaning success in logistic regression (p = 0.004). The proportion of the EEG frequency bands (RB, RA RT, RD) of the entire EEG power spectrum was not significantly different between SE and FE patients. Higher fluctuations in qEEG frequency bands, reflecting greater fluctuation in alertness, during the hours before cessation of MV were associated with a higher rate of complications after extubation in this cohort. The stability of qEEG power values may represent a non-invasive, examiner-independent parameter to facilitate weaning assessment in neurocritical patients.

Electroencephalography in delirium assessment: a scoping review

BACKGROUND

Delirium is a common disorder affecting around 31% of patients in the intensive care unit (ICU). Delirium assessment scores such as the Confusion Assessment Method (CAM) are time-consuming, they cannot differentiate between different types of delirium and their etiologies, and they may have low sensitivities in the clinical setting. While today, electroencephalography (EEG) is increasingly being applied to delirious patients in the ICU, a lack of clear cut EEG signs, leads to inconsistent assessments.

METHODS

We therefore conducted a scoping review on EEG findings in delirium. One thousand two hundred thirty-six articles identified through database search on PubMed and Embase were reviewed. Finally, 33 original articles were included in the synthesis.

RESULTS

EEG seems to offer manifold possibilities in diagnosing delirium. All 33 studies showed a certain degree of qualitative or quantitative EEG alterations in delirium. Thus, normal routine (rEEG) and continuous EEG (cEEG) make presence of delirium very unlikely. All 33 studies used different research protocols to at least some extent. These include differences in time points, duration, conditions, and recording methods of EEG, as well as different patient populations, and diagnostic methods for delirium. Thus, a quantitative synthesis and common recommendations are so far elusive.

CONCLUSION

Future studies should compare the different methods of EEG recording and evaluation to identify robust parameters for everyday use. Evidence for quantitative bi-electrode delirium detection based on increased relative delta power and decreased beta power is growing and should be further pursued. Additionally, EEG studies on the evolution of a delirium including patient outcomes are needed.

Comparison of delirium detection tools in acute care : A rapid review

Background

Delirium is a frequent psychopathological syndrome in geriatric patients. It is sometimes the only symptom of acute illness and bears a high risk for complications. Therefore, feasible assessments are needed for delirium detection.

Objective and methods

Rapid review of available delirium assessments based on a current Medline search and cross-reference check with a special focus on those implemented in acute care hospital settings.

Results

A total of 75 delirium detection tools were identified. Many focused on inattention as well as acute onset and/or fluctuating course of cognitive changes as key features for delirium. A range of assessments are based on the confusion assessment method (CAM) that has been adapted for various clinical settings. The need for a collateral history, time resources and staff training are major challenges in delirium assessment. Latest tests address these through a two-step approach, such as the ultrabrief (UB) CAM or by optional assessment of temporal aspects of cognitive changes (4 As test, 4AT). Most delirium screening assessments are validated for patient interviews, some are suitable for monitoring delirium symptoms over time or diagnosing delirium based on collateral history only.

Conclusion

Besides the CAM the 4AT has become well-established in acute care because of its good psychometric properties and practicability. There are several other instruments extending and improving the possibilities of delirium detection in different clinical settings.

Supplementary Information

The online version of this article (10.1007/s00391-021-02003-5) contains supplementary material, which is available to authorized users.

Physiological Assessment of Delirium Severity: The Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S)

OBJECTIVES

Delirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a tool that can help close this diagnostic gap: the Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).

DESIGN

Retrospective cohort study.

SETTING

Single-center tertiary academic medical center.

PATIENTS

Three-hundred seventy-three adult patients undergoing electroencephalography to evaluate altered mental status between August 2015 and December 2019.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We developed the E-CAM-S based on a learning-to-rank machine learning model of forehead electroencephalography signals. Clinical delirium severity was assessed using the Confusion Assessment Method Severity (CAM-S). We compared associations of E-CAM-S and CAM-S with hospital length of stay and inhospital mortality. E-CAM-S correlated with clinical CAM-S (R = 0.67; p < 0.0001). For the overall cohort, E-CAM-S and CAM-S were similar in their strength of association with hospital length of stay (correlation = 0.31 vs 0.41, respectively; p = 0.082) and inhospital mortality (area under the curve = 0.77 vs 0.81; p = 0.310). Even when restricted to noncomatose patients, E-CAM-S remained statistically similar to CAM-S in its association with length of stay (correlation = 0.37 vs 0.42, respectively; p = 0.188) and inhospital mortality (area under the curve = 0.83 vs 0.74; p = 0.112). In addition to previously appreciated spectral features, the machine learning framework identified variability in multiple measures over time as important features in electroencephalography-based prediction of delirium severity.

CONCLUSIONS

The E-CAM-S is an automated, physiologic measure of delirium severity that predicts clinical outcomes with a level of performance comparable to conventional interview-based clinical assessment.

Opioid Use Increases the Risk of Delirium in Critically Ill Adults Independently of Pain

Rationale: It is unclear whether opioid use increases the risk of ICU delirium. Prior studies have not accounted for confounding, including daily severity of illness, pain, and competing events that may preclude delirium detection.Objectives: To evaluate the association between ICU opioid exposure, opioid dose, and delirium occurrence.Methods: In consecutive adults admitted for more than 24 hours to the ICU, daily mental status was classified as awake without delirium, delirium, or unarousable. A first-order Markov model with multinomial logistic regression analysis considered four possible next-day outcomes (i.e., awake without delirium, delirium, unarousable, and ICU discharge or death) and 11 delirium-related covariables (baseline: admission type, age, sex, Acute Physiology and Chronic Health Evaluation IV score, and Charlson comorbidity score; daily: ICU day, modified Sequential Organ Failure Assessment, ventilation use, benzodiazepine use, and severe pain). This model was used to quantify the association between opioid use, opioid dose, and delirium occurrence the next day.Measurements and Main Results: The 4,075 adults had 26,250 ICU days; an opioid was administered on 57.0% (n = 14,975), severe pain occurred on 7.0% (n = 1,829), and delirium occurred on 23.5% (n = 6,176). Severe pain was inversely associated with a transition to delirium (odds ratio [OR] 0.72; 95% confidence interval [CI], 0.53-0.97). Any opioid administration in awake patients without delirium was associated with an increased risk for delirium the next day [OR, 1.45; 95% CI, 1.24-1.69]. Each daily 10-mg intravenous morphine-equivalent dose was associated with a 2.4% increased risk for delirium the next day.Conclusions: The receipt of an opioid in the ICU increases the odds of transitioning to delirium in a dose-dependent fashion.

Delirium and long term cognition in critically ill patients

Delirium, a form of acute brain dysfunction, is very common in the critically ill adult patient population. Although its pathophysiology is poorly understood, multiple factors associated with delirium have been identified, many of which are coincident with critical illness. To date, no drug or non-drug treatments have been shown to improve outcomes in patients with delirium. Clinical trials have provided a limited understanding of the contributions of multiple triggers and processes of intensive care unit (ICU) acquired delirium, making identification of therapies difficult. Delirium is independently associated with poor long term outcomes, including persistent cognitive impairment. A longer duration of delirium is associated with worse long term cognition after adjustment for age, education, pre-existing cognitive function, severity of illness, and exposure to sedatives. Interestingly, differences in prevalence are seen between ICU survivor populations, with survivors of acute respiratory distress syndrome experiencing higher rates of cognitive impairment at early follow-up compared with mixed ICU survivor populations. Although cognitive performance improves over time for some ICU survivors, impairment is persistent in others. Studies have so far been unable to identify patients at higher risk of long term cognitive impairment; this is an active area of scientific investigation.

Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

Current methods for screening and detecting delirium are not practical in clinical settings. We previously showed that a simplified EEG with bispectral electroencephalography (BSEEG) algorithm can detect delirium in elderly inpatients. In this study, we performed a post-hoc BSEEG data analysis using larger sample size and performed topological data analysis to improve the BSEEG method. Data from 274 subjects included in the previous study were analyzed as a 1st cohort. Subjects were enrolled at the University of Iowa Hospitals and Clinics (UIHC) between January 30, 2016, and October 30, 2017. A second cohort with 265 subjects was recruited between January 16, 2019, and August 19, 2019. The BSEEG score was calculated as a power ratio between low frequency to high frequency using our newly developed algorithm. Additionally, Topological data analysis (TDA) score was calculated by applying TDA to our EEG data. The BSEEG score and TDA score were compared between those patients with delirium and without delirium. Among the 274 subjects from the first cohort, 102 were categorized as delirious. Among the 206 subjects from the second cohort, 42 were categorized as delirious. The areas under the curve (AUCs) based on BSEEG score were 0.72 (1st cohort, Fp1-A1), 0.76 (1st cohort, Fp2-A2), and 0.67 (2nd cohort). AUCs from TDA were much higher at 0.82 (1st cohort, Fp1-A1), 0.84 (1st cohort, Fp2-A2), and 0.78 (2nd cohort). When sensitivity was set to be 0.80, the TDA drastically improved specificity to 0.66 (1st cohort, Fp1-A1), 0.72 (1st cohort, Fp2-A2), and 0.62 (2nd cohort), compared to 0.48 (1st cohort, Fp1-A1), 0.54 (1st cohort, Fp2-A2), and 0.46 (2nd cohort) with BSEEG. BSEEG has the potential to detect delirium, and TDA is helpful to improve the performance.

Investigating how electroencephalogram measures associate with delirium: A systematic review

Delirium is a common neurocognitive disorder in hospital settings, characterised by fluctuating impairments in attention and arousal following an acute precipitant. Electroencephalography (EEG) is a useful method to understand delirium pathophysiology. We performed a systematic review to investigate associations between delirium and EEG measures recorded prior, during, and after delirium. A total of 1,655 articles were identified using PsycINFO, Embase and MEDLINE, 31 of which satisfied inclusion criteria. Methodological quality assessment was undertaken, resulting in a mean quality score of 4 out of a maximum of 5. Qualitative synthesis revealed EEG slowing and reduced functional connectivity discriminated between those with and without delirium (i.e. EEG during delirium); the opposite pattern was apparent in children, with cortical hyperexcitability. EEG appears to have utility in differentiating those with and without delirium, but delirium vulnerability and the long-term effects on brain function require further investigation. Findings provide empirical support for the theory that delirium is a disorder of reduced functional brain integration.

Frontal electroencephalogram activity during emergence from general anaesthesia in children with and without emergence delirium

BACKGROUND

Emergence delirium (ED) in children after general anaesthesia causes significant distress in patients, their family members, and clinicians; however, electroencephalogram (EEG) markers predicting ED have not been fully investigated.

METHODS

This prospective, single-centre observational study enrolled children aged 2-10 yr old under sevoflurane anaesthesia. ED was assessed according to Diagnostic and Statistical Manual of Mental Disorders (DSM) IV or 5 criteria. The relative power of low-frequency (delta and theta) and high-frequency (alpha and beta) EEG waves during the emergence period was compared between the children with and without ED. The linear relationships between the relative power and peak Paediatric Assessment of Emergence Delirium (PAED) score were investigated.

RESULTS

Among the 60 patients, 22 developed ED (ED group), whereas the other 38 did not (non-ED group). The relative power of the delta wave was higher (mean [standard deviation], 0.579 [0.083] vs 0.453 [0.090], respectively, P<0.001) in the ED group, whereas that of the alpha and beta waves was lower in the ED group, than in the non-ED group (0.155 [0.063] vs 0.218 [0.088], P=0.005 and 0.114 [0.069] vs 0.186 [0.070], P<0.001, respectively). The areas under the receiver operating characteristic curves of the relative power of the delta wave, low-to-high frequency power ratio, and delta-to-alpha ratio were 0.837 (95% confidence interval, 0.737-0.938), 0.835 (0.735-0.934), and 0.768 (0.649-0.887), respectively. The relative power of the delta wave and the two ratios had a positive linear relationship with the peak PAED scores.

CONCLUSIONS

Paediatric patients developing ED have increased low-frequency (delta) frontal EEG activity with reduced high-frequency (alpha and beta) activity during emergence from general anaesthesia.

CLINICAL TRIAL REGISTRATION

NCT03797274.

Bispectral Index Monitoring With Density Spectral Array for Delirium Detection

BACKGROUND

Delirium in hospitalized patients often goes undetected. Cerebral state monitors, which measure limited-channel electroencephalography, have shown potential for improving delirium detection.

OBJECTIVE

The aim of this study was to compare an FDA-approved cerebral state monitor, bispectral index monitoring with density spectral array (DSA), for delirium identification with clinical screening methods.

METHODS

Hospitalized patients receiving psychiatric consultation were assessed for delirium using the 3-minute Diagnostic Interview for Confusion Assessment Method (3D-CAM) and underwent bispectral index monitor + DSA monitoring. Visual inspection of frequency band power of the DSA was performed by 2 trained independent raters. Average hue values were calculated for each frequency band using image analysis software as the device did not allow for extraction of raw electroencephalography data. Delirious versus nondelirious group averages, sensitivity, specificity, and area under the curve were calculated for significant DSA variables and the 3D-CAM.

RESULTS

In an initial cohort of 43 patients, visual ratings of the DSA were not associated with delirium (P > 0.1). In a larger cohort of 123 subjects, multiple band hue ratios were associated with delirium, although none survived correction for multiple comparisons. In a subgroup of 74 non-neurological patients, low theta/low delta ratio was significantly associated with delirium (P = 0.001) (sensitivity/specificity/area under the curve: 83%/70%/0.757; 3D-CAM: 67%/77%/0.717; paired-sample area under the curve difference: -0.040, P = 0.68). In 21 patients with dementia, low theta power demonstrated significantly greater sensitivity/specificity/area under the curve of 83%/78%/0.824, whereas 3D-CAM achieved 50%/78%/0.639 (P = 0.04).

CONCLUSION

Bispectral index monitor + DSA was similar to 3D-CAM for detecting delirium in hospitalized patients with and without neurological disorders, and was significantly more accurate in patients with dementia. More studies are needed to validate the use of cerebral state monitors for quantitative delirium detection.

Double standard: why electrocardiogram is standard care while electroencephalogram is not?

PURPOSE OF REVIEW

Major adverse cardiovascular and cerebrovascular events (MACCE) significantly affect the surgical outcomes. Electrocardiogram (ECG) has been a standard intraoperative monitor for 30 years. Electroencephalogram (EEG) can provide valuable information about the anesthetized state and guide anesthesia management during surgery. Whether EEG should be a standard intraoperative monitor is discussed in this review.

RECENT FINDINGS

Deep anesthesia has been associated with postoperative delirium, especially in elderly patients. Intraoperative EEG monitoring has been demonstrated to reduce total anesthesia drug use during general anesthesia and postoperative delirium.

SUMMARY

Unlike ECG monitoring, the EEG under general anesthesia has not been designated as a standard monitor by anesthesiologist societies around the world. The processed EEG technology has been commercially available for more than 25 years and EEG technology has significantly facilitated its intraoperative use. It is time to consider EEG as a standard anesthesia monitor during surgery.

Electroencephalography: Clinical Applications During the Perioperative Period

Electroencephalography (EEG) monitoring has become technically feasible in daily clinical anesthesia practice. EEG is a sensitive method for detecting neurophysiological changes in the brain and represents an important frontier in the monitoring and treatment of patients in the perioperative period. In this review, we briefly introduce the essential principles of EEG. We review EEG application during anesthesia practice in the operating room, including the use of processed EEG in depth of anesthesia assessment, raw EEG monitoring in recognizing brain states under different anesthetic agents, the use of EEG in the prevention of perioperative neurocognitive disorders and detection of cerebral ischemia. We then discuss EEG utilization in the intensive care units, including the use of EEG in sedative level titration and prognostication of clinical outcomes. Existing literature provides insight into both the advances and challenges of the clinical applications of EEG. Future study is clearly needed to elucidate the precise EEG features that can reliably optimize perioperative care for individual patients.

Implementation of strategies to prevent and treat postoperative delirium in the post-anesthesia caring unit : A German survey of current practice

Postoperative delirium is associated with worse outcome. The aim of this study was to understand present strategies for delirium screening and therapy in German Post-Anesthesia-Caring-Units (PACU). We designed a German-wide web-based questionnaire which was sent to 922 chairmen of anesthesiologic departments and to 726 anesthetists working in ambulatory surgery. The response rate was 30% for hospital anesthesiologists. 10% (95%-confidence interval: 8–12) of the anesthesiologists applied a standardised screening for delirium. Even though not on a regular basis, in 44% (41–47) of the hospitals, a recommended and validated screening was used, the Nursing Delirium Screening Scale (NuDesc) or the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). If delirium was likely to occur, 46% (43–50) of the patients were examined using a delirium tool. 20% (17–23) of the patients were screened in intensive care units. For the treatment of delirium, alpha-2-agonists (83%, 80–85) were used most frequently for vegetative symptoms, benzodiazepines for anxiety in 71% (68–74), typical neuroleptics in 77% (71–82%) of patients with psychotic symptoms and in 20% (15–25) in patients with hypoactive delirium. 45% (39–51) of the respondents suggested no therapy for this entity. Monitoring of delirium is not established as a standard procedure in German PACUs. However, symptom-oriented therapy for postoperative delirium corresponds with current guidelines.

A roadmap to advance delirium research: Recommendations from the NIDUS Scientific Think Tank

Delirium is an acute disorder of attention and cognition. It occurs across the life span, yet it is particularly common among older adults, and is closely linked with underlying neurocognitive disorders. Evidence is mounting that intervening on delirium may represent an important opportunity for delaying the onset or progression of dementia. To accelerate the current understanding of delirium, the Network for Investigation of Delirium: Unifying Scientists (NIDUS) held a conference “Advancing Delirium Research: A Scientific Think Tank” in June 2019. This White Paper encompasses the major knowledge and research gaps identified at the conference: advancing delirium definition and measurement, understanding delirium pathophysiology, and prevention and treatment of delirium. A roadmap of research priorities is proposed to advance the field in a systematic, interdisciplinary, and coordinated fashion. A call is made for an international consortium and biobank targeted to delirium, as well as a public health campaign to advance the field.

Neuroanesthesiology Update

This review is intended to provide a summary of the literature pertaining to the perioperative care of neurosurgical patients and patients with neurological diseases. General topics addressed in this review include general neurosurgical considerations, stroke, neurological monitoring, and perioperative disorders of cognitive function.