Predisposition for delirium and EEG characteristics

Neurophenomenological Investigation of Mindfulness Meditation "Cessation" Experiences Using EEG Network Analysis in an Intensively Sampled Adept Meditator

Mindfulness meditation is a contemplative practice that is informed by Buddhism. It has been proven effective for improving mental and physical health in clinical and non-clinical contexts. To date, mainstream dialogue and scientific research on mindfulness has focused primarily on short-term mindfulness training and applications of mindfulness for reducing stress. Understanding advanced mindfulness practice has important implications for mental health and general wellbeing. According to Theravada Buddhist meditation, a "cessation" event is a dramatic experience of profound clarity and equanimity that involves a complete discontinuation in experience, and is evidence of mastery of mindfulness meditation. Thirty-seven cessation events were captured in a single intensively sampled advanced meditator (over 6,000 h of retreat mindfulness meditation training) while recording electroencephalography (EEG) in 29 sessions between November 12, 2019 and March 11, 2020. Functional connectivity and network integration were assessed from 40 s prior to cessations to 40 s after cessations. From 21 s prior to cessations there was a linear decrease in large-scale functional interactions at the whole-brain level in the alpha band. In the 40 s following cessations these interactions linearly returned to prior levels. No modulation of network integration was observed. The decrease in whole-brain functional connectivity was underlain by frontal to left temporal and to more posterior decreases in connectivity, while the increase was underlain by wide-spread increases in connectivity. These results provide neuroscientific evidence of large-scale modulation of brain activity related to cessation events that provides a foundation for future studies of advanced meditation.

Effect of prolonged sedation with dexmedetomidine, midazolam, propofol, and sevoflurane on sleep homeostasis in rats

BACKGROUND

Sleep disruption is a common occurrence during medical care and is detrimental to patient recovery. Long-term sedation in the critical care setting is a modifiable factor that affects sleep, but the impact of different sedative-hypnotics on sleep homeostasis is not clear.

METHODS

We conducted a systematic comparison of the effects of prolonged sedation (8 h) with i.v. and inhalational agents on sleep homeostasis. Adult Sprague-Dawley rats (n=10) received dexmedetomidine or midazolam on separate days. Another group (n=9) received propofol or sevoflurane on separate days. A third group (n=12) received coadministration of dexmedetomidine and sevoflurane. Wakefulness (wake), slow-wave sleep (SWS), and rapid eye movement (REM) sleep were quantified during the 48-h post-sedation period, during which we also assessed wake-associated neural dynamics using two electroencephalographic measures: theta-high gamma phase-amplitude coupling and high gamma weighted phase-lag index.

RESULTS

Dexmedetomidine-, midazolam-, or propofol-induced sedation increased wake and decreased SWS and REM sleep (P<0.0001) during the 48-h post-sedation period. Sevoflurane produced no change in SWS, decreased wake for 3 h, and increased REM sleep for 6 h (P<0.02) post-sedation. Coadministration of dexmedetomidine and sevoflurane induced no change in wake (P>0.05), increased SWS for 3 h, and decreased REM sleep for 9 h (P<0.02) post-sedation. Dexmedetomidine, midazolam, and coadministration of dexmedetomidine with sevoflurane reduced wake-associated phase-amplitude coupling (P≤0.01). All sedatives except sevoflurane decreased wake-associated high gamma weighted phase-lag index (P<0.01).

CONCLUSIONS

In contrast to i.v. drugs, prolonged sevoflurane sedation produced minimal changes in sleep homeostasis and neural dynamics. Further studies are warranted to assess inhalational agents for long-term sedation and sleep homeostasis.

Lower alpha frequency of intraoperative frontal EEG is associated with postoperative delirium: A secondary propensity-matched analysis

BACKGROUND

Postoperative delirium (POD) is a serious complication of surgery, especially in the elderly patient population. It has been proposed that decreasing the amount of anesthetics by titrating to an EEG index will lower POD rate, but clear evidence is missing. A strong age-dependent negative correlation has been reported between the peak oscillatory frequency of alpha waves and end-tidal anesthetic concentration, with older patients generating slower alpha frequencies. We hypothesized, that slower alpha oscillations are associated with a higher rate of POD.

METHOD

Retrospective analysis of patients` data from a prospective observational study in cardiac surgical patients approved by the Bernese Ethics committee. Frontal EEG was recorded during Isoflurane effect-site concentrations of 0.7 to 0.8 and peak alpha frequency was measured at highest power between 6 and 17 Hz. Delirium was assessed by chart review. Demographic and clinical characteristics were compared between POD and non-POD groups. Selection bias was addressed using nearest neighbor propensity score matching (PSM) for best balance. This incorporated 18 variables, whereas patients with missing variable information or without an alpha oscillation were excluded.

RESULT

Of the 1072 patients in the original study, 828 were included, 73 with POD, 755 without. PSM allowed 328 patients into the final analysis, 67 with, 261 without POD. Before PSM, 8 variables were significantly different between POD and non-POD groups, none thereafter. Mean peak alpha frequency was significantly lower in the POD in contrast to non-POD group before and after matching (7.9 vs 8.9 Hz, 7.9 vs 8.8 Hz respectively, SD 1.3, p < 0.001).

CONCLUSION

Intraoperative slower frontal peak alpha frequency is independently associated with POD after cardiac surgery and may be a simple intraoperative neurophysiological marker of a vulnerable brain for POD. Further studies are needed to investigate if there is a causal link between alpha frequency and POD.

Preoperative electroencephalographic alpha-power changes with eyes opening are associated with postoperative attention impairment and inattention-related delirium severity

BACKGROUND

In the eyes-closed, awake condition, EEG oscillatory power in the alpha band (7-13 Hz) dominates human spectral activity. With eyes open, however, EEG alpha power substantially decreases. Less alpha attenuation with eyes opening has been associated with inattention; thus, we analysed whether reduced preoperative alpha attenuation with eyes opening is associated with postoperative inattention, a delirium-defining feature.

METHODS

Preoperative awake 32-channel EEG was recorded with eyes open and eyes closed in 71 non-neurological, noncardiac surgery patients aged ≥ 60 years. Inattention and other delirium features were assessed before surgery and twice daily after surgery until discharge. Eyes-opening EEG alpha-attenuation magnitude was analysed for associations with postoperative inattention, primarily, and with delirium severity, secondarily, using multivariate age- and Mini-Mental Status Examination (MMSE)-adjusted logistic and proportional-odds regression analyses.

RESULTS

Preoperative alpha attenuation with eyes opening was inversely associated with postoperative inattention (odds ratio [OR] 0.73, 95% confidence interval [CI]: 0.57, 0.94; P=0.038). Sensitivity analyses showed an inverse relationship between alpha-attenuation magnitude and inattention chronicity, defined as 'never', 'newly', or 'chronically' inattentive (OR 0.76, 95% CI: 0.62, 0.93; P=0.019). In addition, preoperative alpha-attenuation magnitude was inversely associated with postoperative delirium severity (OR 0.79, 95% CI: 0.65, 0.95; P=0.040), predominantly as a result of the inattention feature.

CONCLUSIONS

Preoperative awake, resting, EEG alpha attenuation with eyes opening might represent a neural biomarker for risk of postoperative attentional impairment. Further, eyes-opening alpha attenuation could provide insight into the neural mechanisms underlying postoperative inattention risk.

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.

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.

Extremes of baseline cognitive function determine the severity of delirium: a population study

Although delirium is a significant clinical and public health problem, little is understood about how specific vulnerabilities underlie the severity of its presentation. Our objective was to quantify the relationship between baseline cognition and subsequent delirium severity. We prospectively investigated a population-representative sample of 1510 individuals aged ≥70 years, of whom 209 (13.6%) were hospitalized across 371 episodes (1999 person-days assessment). Baseline cognitive function was assessed using the modified Telephone Interview for Cognitive Status, supplemented by verbal fluency measures. We estimated the relationship between baseline cognition and delirium severity [Memorial Delirium Assessment Scale (MDAS)] and abnormal arousal (Observational Scale of Level of Arousal), adjusted by age, sex, frailty and illness severity. We conducted further analyses examining presentations to specific hospital settings and common precipitating aetiologies. The median time from baseline cognitive assessment to admission was 289 days (interquartile range 130 to 47 days). In admitted patients, delirium was present on at least 1 day in 45% of admission episodes. The average number of days with delirium (consecutively positive assessments) was 3.9 days. Elective admissions accounted for 88 bed days (4.4%). In emergency (but not elective) admissions, we found a non-linear U-shaped relationship between baseline global cognition and delirium severity using restricted cubic splines. Participants with baseline cognition 2 standard deviations below average (z-score = -2) had a mean MDAS score of 14 points (95% CI 10 to 19). Similarly, those with baseline cognition z-score = + 2 had a mean MDAS score of 7.9 points (95% CI 4.9 to 11). Individuals with average baseline cognition had the lowest MDAS scores. The association between baseline cognition and abnormal arousal followed a comparable pattern. C-reactive protein ≥20 mg/l and serum sodium <125 mM/l were associated with more severe delirium. Baseline cognition is a critical determinant of the severity of delirium and associated changes in arousal. Emergency admissions with lowest and highest baseline cognition who develop delirium should receive enhanced clinical attention.

How to Study the Brain While Anesthetizing It?! A Scoping Review on Running Neuroanesthesiologic Studies and Trials That Include Neurosurgical Patients

This scoping review addresses the challenges of neuroanesthesiologic research: the population, the methods/treatment/exposure, and the outcome/results. These challenges are put into the context of a future research agenda for peri-/intraoperative anesthetic management, neurocritical care, and applied neurosciences. Finally, the opportunities of adaptive trial design in neuroanesthesiologic research are discussed.

Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction

Physiologic signals such as the electroencephalogram (EEG) demonstrate irregular behaviors due to the interaction of multiple control processes operating over different time scales. The complexity of this behavior can be quantified using multi-scale entropy (MSE). High physiologic complexity denotes health, and a loss of complexity can predict adverse outcomes. Since postoperative delirium is particularly hard to predict, we investigated whether the complexity of preoperative and intraoperative frontal EEG signals could predict postoperative delirium and its endophenotype, inattention. To calculate MSE, the sample entropy of EEG recordings was computed at different time scales, then plotted against scale; complexity is the total area under the curve. MSE of frontal EEG recordings was computed in 50 patients ≥ age 60 before and during surgery. Average MSE was higher intra-operatively than pre-operatively (p = 0.0003). However, intraoperative EEG MSE was lower than preoperative MSE at smaller scales, but higher at larger scales (interaction p < 0.001), creating a crossover point where, by definition, preoperative, and intraoperative MSE curves met. Overall, EEG complexity was not associated with delirium or attention. In 42/50 patients with single crossover points, the scale at which the intraoperative and preoperative entropy curves crossed showed an inverse relationship with delirium-severity score change (Spearman ρ = -0.31, p = 0.054). Thus, average EEG complexity increases intra-operatively in older adults, but is scale dependent. The scale at which preoperative and intraoperative complexity is equal (i.e., the crossover point) may predict delirium. Future studies should assess whether the crossover point represents changes in neural control mechanisms that predispose patients to postoperative delirium.

Current Challenges in the Recognition and Management of Delirium Superimposed on Dementia

Delirium occurring in a patient with preexisting dementia is referred to as delirium superimposed on dementia (DSD). DSD commonly occurs in older hospitalized patients and is associated with worse outcomes, including higher rates of mortality and institutionalization, compared to inpatients with delirium or dementia alone. This narrative review summarizes the screening, diagnosis, management, and pathophysiology of DSD and concludes by highlighting opportunities for future research. Studies were identified via Medline and PsycINFO keyword search, and handsearching reference lists. Conceptually, DSD could be considered an "acute exacerbation" of dementia precipitated by a noxious insult akin to an acute exacerbation of heart failure or acute on chronic renal failure. However, unlike other organ systems, there are no established biomarkers for delirium, so DSD is diagnosed and monitored clinically. Because cognitive dysfunction is common to both delirium and dementia, the diagnosis of DSD can be challenging. Inattention, altered levels of arousal, and motor dysfunction may help distinguish DSD from dementia alone. An informant history suggestive of an acute change in cognition or alertness should be investigated and managed as delirium until proven otherwise. The key management principles include prevention, identifying and treating the underlying precipitant(s), implementing multicomponent interventions to create an ideal environment for brain recovery, preventing complications, managing distress, and monitoring for resolution. Informing and involving family members or caregivers throughout the patient journey are essential because there is significant prognostic uncertainty, including the risk of persistent cognitive and functional decline following DSD and relapse. Furthermore, informal carers can provide significant assistance in management. Emerging evidence demonstrates that increased exposure to delirium is associated with neuronal injury and worse cognitive outcomes although the mechanisms through which this occurs remain unclear. Given the clinical overlap between delirium and dementia, studying shared pathophysiological pathways may uncover diagnostic tests and is an essential step in therapeutic innovation.

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.

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

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Predisposing risk is not associated with delirium-related fMRI characteristics.

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Older age within an elderly cohort is related to higher functional connectivity strength.

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This relation is in opposite direction than hypothesized.

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The onset of delirium may reflect new functional network impairments.

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 (β = 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.