Electroencephalography and delirium in the postoperative period

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.

EEG and acute confusional state at the emergency department

OBJECTIVES

Acute confusional state (ACS) is a common cause of admission to the emergency department (ED). It can be related to numerous etiologies. Electroencephalography (EEG) can show specific abnormalities in cases of non-convulsive status epilepticus (NCSE), or metabolic or toxic encephalopathy. However, up to 80% of patients with a final diagnosis of NCSE have an ACS initially attributed to another cause. The exact place of EEG in the diagnostic work-up remains unclear.

METHODS

Data of consecutive patients admitted to the ED for an ACS in a two-year period and who were referred for an EEG were collected. The initial working diagnosis was based on medical history, clinical, biological and imaging investigations allowing classification into four diagnostic categories. Comparison to the final diagnosis was performed after EEG recordings (and sometimes additional tests) were performed, which allowed the reclassification of some patients from one category to another.

RESULTS

Seventy-five patients (mean age: 71.1 years) were included with the following suspected diagnoses: seizures for 8 (11%), encephalopathy for 14 (19%), other cause for 34 (45%) and unknown for 19 (25%). EEG was recorded after a mean of 1.5 days after symptom onset, and resulted in the reclassification of patients as follows: seizure for 15 (20%), encephalopathy for 15 (20%), other cause for 29 (39%) and unknown cause for 16 (21%). Moreover, ongoing epileptic activity (NCSE or seizure) and interictal epileptiform activity were found in eight (11%) patients initially diagnosed in another category.

DISCUSSION

In our cohort, EEG was a key examination in the management strategy of ACS in 11% of patients admitted to the ED. It resulted in a diagnosis of epilepsy in these patients admitted with unusual confounding presentations.

Mitochondrial Dysfunction of Peripheral Platelets as a Predictive Biomarker for Postoperative Delirium in Elderly Patients

OBJECTIVE

To determine the association between the preoperative Bioenergetic Health Index (BHI) of platelets and the occurrence of postoperative delirium (POD) in elderly patients.

METHODS

Elderly patients scheduled for major abdominal surgery under general anesthesia were included. The presence of POD was assessed within the 3 days after surgery. Seahorse XF analysis and transmission electron microscopy were utilized to evaluate the mitochondrial metabolism and morphology of platelets.

RESULTS

A total of 20 out of 162 participants developed POD. Participants with POD showed lower preoperative Mini-Mental State Examination scores and total protein levels, fewer educational years, longer surgery duration, higher mean platelet volume, and lower platelet BHI compared with those without POD. Damaged mitochondria with swollen appearance and distorted cristae was detected in platelets from participants with POD. Preoperative platelet BHI was independently associated with the occurrence of POD after adjusting for age, education, preoperative Mini-Mental State Examination score, preoperative mean platelet volume and total protein levels, surgical type and duration, and lymphocyte counts on the first postoperative day (OR 0.11, 95% CI 0.03-0.37, p < 0.001). The areas under the receiver operating curves for predicting POD were 0.83 (95% CI 0.76-0.88) for platelet BHI. It showed a sensitivity of 85.00% and specificity of 73.24%, with an optimal cutoff value of 1.61. Using a serial combination (mean platelet volume followed by BHI) yielded a sensitivity of 80.00% and specificity of 82.39%.

INTERPRETATION

Preoperative platelet BHI was independently associated with the occurrence of POD in elderly patients and has the potential as a screening biomarker for POD risk. ANN NEUROL 2024;96:74-86.

A Novel Preoperative Electroencephalogram-Derived Index to Predict Early Postoperative Delirium in Elderly Patients After Hip Fracture Surgeries: Development of a Prediction Model

Introduction

It is appealing to accurately predict postoperative delirium (POD) before surgeries. In this study, it was hypothesized that a novel electroencephalogram-derived index, the delirium index (DELi), could extract latent information regarding the predisposing factors of POD preoperatively. This study was aimed at developing a concise model that incorporated this DELi score to predict the early POD of elderly patients after hip surgeries.

Materials and Methods

Elderly patients scheduled for elective hip fracture surgeries were prospectively enrolled in a tertiary care hospital from November 2020 to June 2022. DELi scores and patient characteristics (age, sex, types of fracture and surgery, the time interval between fracture and surgery, cognitive function assessed using the Montreal Cognitive Assessment (MoCA), and frailty status assessed using the FRAIL scale) were collected preoperatively as candidate predictors. POD diagnosed using the confusion assessment method (CAM) was the outcome. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select predictors. Then, these predictors were entered into a backward logistical regression analysis to develop a prediction model. Discrimination, calibration and clinical utility were validated using the bootstrapping method.

Results

All data (144 qualified patients of 170) were used for development. POD was observed in 71 patients (49.3%). Preoperative DELi scores predicted early POD (the area under the curve (AUC) = .786, 95% confidence interval (CI): .712, .860, in internal validation). A nomogram with MoCA, FRAIL scale and DELi score was constructed with excellent discrimination (AUC = .920, 95% CI: .876, .963, in internal validation), accredited calibration (P = .733, Hosmer‒Lemeshow test), and a wide range of threshold probabilities (5% to 95%).

Conclusions

Preoperative DELi scores predicted the early POD of elderly patients after hip surgeries. A concise prediction model was developed and demonstrated excellent discrimination.

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.

Differential effects of sevoflurane and desflurane on frontal intraoperative electroencephalogram dynamics associated with postoperative delirium

STUDY OBJECTIVE

Intraoperative electroencephalogram (EEG) patterns associated with postoperative delirium (POD) development have been studied, but the differences in EEG recordings between sevoflurane- and desflurane-induced anesthesia have not been clarified. We aimed to distinguish the EEG characteristics of sevoflurane and desflurane in relation to POD development.

DESIGN AND PATIENTS

We collected frontal four-channel EEG data during the maintenance of anesthesia from 148 elderly patients who received sevoflurane (n = 77) or desflurane (n = 71); 30 patients were diagnosed with delirium postoperatively. The patients were divided into four subgroups based on anesthetics and delirium status: sevoflurane delirium (n = 17), sevoflurane non-delirium (n = 60), desflurane delirium (n = 13), and desflurane non-delirium (n = 58). We compared spectral power, coherence, and pairwise phase consistency (PPC) between sevoflurane and desflurane, and between non-delirium and delirium groups for each anesthetic.

MAIN RESULTS

In patients without POD, the sevoflurane non-delirium group exhibited higher EEG spectral power across 8.5-35 Hz (99.5% CI bootstrap analysis) and higher PPC from alpha to gamma bands (p < 0.005) compared to the desflurane non-delirium group. Conversely, in patients with POD, no significant EEG differences were observed between the sevoflurane and desflurane delirium groups. For the sevoflurane-induced patients, the sevoflurane delirium group had significantly lower power within 7.5-31.5 Hz (99.5% CI bootstrap analysis), reduced coherence over 8.9-23.8 Hz (99.5% CI bootstrap analysis), and lower PPC values in the alpha band (p < 0.005) compared with the sevoflurane non-delirium group. For the desflurane-induced patients, there were no significant differences in the EEG patterns between delirium and non-delirium groups.

CONCLUSIONS

In normal patients without POD, sevoflurane demonstrates a higher power spectrum and prefrontal connectivity than desflurane. Furthermore, reduced frontal alpha power, coherence, and connectivity of intraoperative EEG could be associated with an increased risk of POD. These intraoperative EEG characteristics associated with POD are more noticeable in sevoflurane-induced anesthesia than in desflurane-induced anesthesia.

Intraoperative EEG-based monitors: are we looking under the lamppost?

PURPOSE OF REVIEW

While electroencephalogram (EEG)-based depth of anesthesia monitors have been in use clinically for decades, there is still a major debate concerning their efficacy for detecting awareness under anesthesia (AUA). Further utilization of these monitors has also been discussed vividly, for example, reduction of postoperative delirium (POD).It seems that with regard to reducing AUA and POD, these monitors might be applicable, under specific anesthetic protocols. But in other settings, such monitoring might be less contributive and may have a 'built-it glass ceiling'.Recent advances in other venues of electrophysiological monitoring might have a strong theoretical rationale, and early supporting results, to offer a breakthrough out of this metaphorical glass ceiling. The purpose of this review is to present this possibility.

RECENT FINDINGS

Following previous findings, it might be concluded that for some anesthesia protocols, the prevailing depth of anesthesia monitors may prevent incidences of AUA and POD. However, in other settings, which may involve other anesthesia protocols, or specifically for POD - other perioperative causes, they may not. Attention-related processes measured by easy-to-use real-time electrophysiological markers are becoming feasible, also under anesthesia, and might be applicable for more comprehensive prevention of AUA, POD and possibly other perioperative complications.

SUMMARY

Attention-related monitoring might have a strong theoretical basis for the prevention of AUA, POD, and potentially other distressing postoperative outcomes, such as stroke and postoperative neurocognitive disorder. There seems to be already some initial supporting evidence in this regard.

The Effect of Central Sensitization on Postoperative Neurocognitive Dysfunction in Hospitalized Elderly Patients: A Prospective Cohort Clinical Trial

OBJECTIVE

To investigate whether central sensitization (CS) in elderly patients was a predictive risk factor for postoperative neurocognitive dysfunction (PNCD).

METHODS

One hundred and thirty-three aged patients undergoing total knee arthroplasty (TKA) who received femoral nerve block and general anesthesia were recruited in this research and prospectively assigned into two groups according to the Central Sensitization Inventory (CSI) score: group C (n = 106, CSI score less than 40) and group CS (n = 27, CSI score higher than 40). Scores of Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Confusion Assessment Method (CAM), Numerical Rating Scale (NRS) and Quality of recovery-40 (QoR-40) questionnaires were assessed. Basic information and clinical records of all participants were also collected.

RESULTS

PNCD occurred in 24 (22.6%) of patients in group C and 16 (59.3%) in group CS (p < .05). Multivariate logistic regression analysis revealed that patients with CSI score ≥40 before surgery exhibited higher risk of PNCD after adjustment for other risk factors (p < .05). Compared to group C, the pre- and post-operative NRS scores, pain duration, the WOMAC score, and propofol consumptions for anesthesia induction were significantly increased in group CS (p < .05).

CONCLUSION

Hospitalized elderly patients with clinical symptoms of CS scores may have increased risk of PNCD following TKA.

Repurposing electroencephalogram monitoring of general anaesthesia for building biomarkers of brain ageing: an exploratory study

Background

Electroencephalography (EEG) is increasingly used for monitoring the depth of general anaesthesia, but EEG data from general anaesthesia monitoring are rarely reused for research. Here, we explored repurposing EEG monitoring from general anaesthesia for brain-age modelling using machine learning. We hypothesised that brain age estimated from EEG during general anaesthesia is associated with perioperative risk.

Methods

We reanalysed four-electrode EEGs of 323 patients under stable propofol or sevoflurane anaesthesia to study four EEG signatures (95% of EEG power <8-13 Hz) for age prediction: total power, alpha-band power (8-13 Hz), power spectrum, and spatial patterns in frequency bands. We constructed age-prediction models from EEGs of a healthy reference group (ASA 1 or 2) during propofol anaesthesia. Although all signatures were informative, state-of-the-art age-prediction performance was unlocked by parsing spatial patterns across electrodes along the entire power spectrum (mean absolute error=8.2 yr; R2=0.65).

Results

Clinical exploration in ASA 1 or 2 patients revealed that brain age was positively correlated with intraoperative burst suppression, a risk factor for general anaesthesia complications. Surprisingly, brain age was negatively correlated with burst suppression in patients with higher ASA scores, suggesting hidden confounders. Secondary analyses revealed that age-related EEG signatures were specific to propofol anaesthesia, reflected by limited model generalisation to anaesthesia maintained with sevoflurane.

Conclusions

Although EEG from general anaesthesia may enable state-of-the-art age prediction, differences between anaesthetic drugs can impact the effectiveness and validity of brain-age models. To unleash the dormant potential of EEG monitoring for clinical research, larger datasets from heterogeneous populations with precisely documented drug dosage will be essential.

Sleep Fragmentation, Electroencephalographic Slowing, and Circadian Disarray in a Mouse Model for Intensive Care Unit Delirium

BACKGROUND

We aimed to further validate our previously published animal model for delirium by testing the hypothesis that in aged mice, Anesthesia, Surgery and simulated ICU conditions (ASI) induce sleep fragmentation, electroencephalographic (EEG) slowing, and circadian disarray consistent with intensive care unit (ICU) patients with delirium.

METHODS

A total of 41 mice were used. Mice were implanted with EEG electrodes and randomized to ASI or control groups. ASI mice received laparotomy, anesthesia, and simulated ICU conditions. Controls did not receive ASI. Sleep was recorded at the end of ICU conditions, and hippocampal tissue was collected on EEG recording. Arousals, EEG dynamics, and circadian gene expression were compared with t tests. Two-way repeated measures analysis of variance (RM ANOVA) was used to assess sleep according to light.

RESULTS

ASI mice experienced frequent arousals (36.6 ± 3.2 vs 26.5 ± 3.4; P = .044; 95% confidence interval [CI], 0.29-19.79; difference in mean ± SEM, 10.04 ± 4.62) and EEG slowing (frontal theta ratio, 0.223 ± 0.010 vs 0.272 ± 0.019; P = .026; 95% CI, -0.091 to -0.007; difference in mean ± SEM, -0.05 ± 0.02) relative to controls. In ASI mice with low theta ratio, EEG slowing was associated with a higher percentage of quiet wakefulness (38.2 ± 3.6 vs 13.4 ± 3.8; P = .0002; 95% CI, -35.87 to -13.84; difference in mean ± SEM, -24.86 ± 5.19). ASI mice slept longer during the dark phases of the circadian cycle (nonrapid eye movement [NREM], dark phase 1 [D1]: 138.9 ± 8.1 minutes vs 79.6 ± 9.6 minutes, P = .0003, 95% CI, -95.87 to -22.69, predicted mean difference ± SE: -59.28 ± 13.89; NREM, dark phase 2 (D2): 159.3 ± 7.3 minutes vs 112.6 ± 15.5 minutes, P = .006, 95% CI, -83.25 to -10.07, mean difference ± SE, -46.66 ± 13.89; rapid eye movement (REM), D1: 20.5 ± 2.1 minutes vs 5.8 ± 0.8 minutes, P = .001, 95% CI, -24.60 to -4.71, mean difference ± SE, -14. 65 ± 3.77; REM, D2: 21.0 ± 2.2 minutes vs 10.3 ± 1.4 minutes, P = .029, 95% CI, -20.64 to -0.76, mean difference ± SE, -10.70 ± 3.77). The expression of essential circadian genes was also lower in ASI mice (basic helix-loop-helix ARNT like [BMAL1] : -1.3 fold change; circadian locomotor output cycles protein kaput [CLOCK] : -1.2).

CONCLUSIONS

ASI mice experienced EEG and circadian changes mimicking those of delirious ICU patients. These findings support further exploration of this mouse approach to characterize the neurobiology of delirium.

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.

Quantitative EEG signatures of delirium and coma in mechanically ventilated ICU patients

OBJECTIVE

To identify quantitative electroencephalography (EEG)-based indicators of delirium or coma in mechanically ventilated patients.

METHODS

We prospectively enrolled 28 mechanically ventilated intensive care unit (ICU) patients to undergo 24-hour continuous EEG, 25 of whom completed the study. We assessed patients twice daily using the Richmond Agitation-Sedation Scale (RASS) and Confusion Assessment Method for the ICU (CAM-ICU). We evaluated the spectral profile, regional connectivity and complexity of 5-minute EEG segments after each assessment. We used penalized regression to select EEG metrics associated with delirium or coma, and compared mixed-effects models predicting delirium with and without the selected EEG metrics.

RESULTS

Delta variability, high-beta variability, relative theta power, and relative alpha power contributed independently to EEG-based identification of delirium or coma. A model with these metrics achieved better prediction of delirium or coma than a model with clinical variables alone (Akaike Information Criterion: 36 vs 43, p = 0.006 by likelihood ratio test). The area under the receiver operating characteristic curve for an ad hoc hypothetical delirium score using these metrics was 0.94 (95%CI 0.83-0.99).

CONCLUSIONS

We identified four EEG metrics that, in combination, provided excellent discrimination between delirious/comatose and non-delirious mechanically ventilated ICU patients.

SIGNIFICANCE

Our findings give insight to neurophysiologic changes underlying delirium and provide a basis for pragmatic, EEG-based delirium monitoring technology.

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.

Altered EEG, disrupted hippocampal long-term potentiation and neurobehavioral deficits implicate a delirium-like state in a mouse model of sepsis

Sepsis and systemic inflammation are often accompanied by severe encephalopathy, sleep disruption and delirium that strongly correlate with poor clinical outcomes including long-term cognitive deficits. The cardinal manifestations of delirium are fluctuating altered mental status and inattention, identified in critically ill patients by interactive bedside assessment. The lack of analogous assessments in mouse models or clear biomarkers is a challenge to preclinical studies of delirium. In this study, we utilized concurrent measures of telemetric EEG recordings and neurobehavioral tasks in mice to characterize inattention and persistent cognitive deficits following polymicrobial sepsis. During the 24-hour critical illness period for the mice, slow-wave EEG dominance, sleep disruption, and hypersensitivity to auditory stimuli in neurobehavioral tasks resembled clinical observations in delirious patients in which alterations in similar outcome measurements, although measured differently in mice and humans, are reported. Mice were tested for nest building ability 7 days after sepsis induction, when sickness behaviors and spontaneous activity had returned to baseline. Animals that showed persistent deficits determined by poor nest building at 7 days also exhibited molecular changes in hippocampal long-term potentiation compared to mice that returned to baseline cognitive performance. Together, these behavioral and electrophysiological biomarkers offer a robust mouse model with which to further probe molecular pathways underlying brain and behavioral changes during and after acute illness such as sepsis.

Neural complexity is a common denominator of human consciousness across diverse regimes of cortical dynamics

What is the common denominator of consciousness across divergent regimes of cortical dynamics? Does consciousness show itself in decibels or in bits? To address these questions, we introduce a testbed for evaluating electroencephalogram (EEG) biomarkers of consciousness using dissociations between neural oscillations and consciousness caused by rare genetic disorders. Children with Angelman syndrome (AS) exhibit sleep-like neural dynamics during wakefulness. Conversely, children with duplication 15q11.2-13.1 syndrome (Dup15q) exhibit wake-like neural dynamics during non-rapid eye movement (NREM) sleep. To identify highly generalizable biomarkers of consciousness, we trained regularized logistic regression classifiers on EEG data from wakefulness and NREM sleep in children with AS using both entropy measures of neural complexity and spectral (i.e., neural oscillatory) EEG features. For each set of features, we then validated these classifiers using EEG from neurotypical (NT) children and abnormal EEGs from children with Dup15q. Our results show that the classification performance of entropy-based EEG biomarkers of conscious state is not upper-bounded by that of spectral EEG features, which are outperformed by entropy features. Entropy-based biomarkers of consciousness may thus be highly adaptable and should be investigated further in situations where spectral EEG features have shown limited success, such as detecting covert consciousness or anesthesia awareness.

Prediction of the development of delirium after transcatheter aortic valve implantation using preoperative brain perfusion SPECT

Objectives

Delirium is an important prognostic factor in postoperative patients undergoing cardiovascular surgery and intervention, including transcatheter aortic valve implantation (TAVI). However, delirium after transcatheter aortic valve implantation (DAT) is difficult to predict and its pathophysiology is still unclear. We aimed to investigate whether preoperative cerebral blood flow (CBF) is associated with DAT and, if so, whether CBF measurement is useful for predicting DAT.

Methods

We evaluated CBF in 50 consecutive patients before TAVI (84.7±4.5 yrs., 36 females) using ^99mTc ethyl cysteinate dimer single-photon emission computed tomography. Preoperative CBF of the DAT group (N = 12) was compared with that of the non-DAT group (N = 38) using whole brain voxel-wise analysis with SPM12 and region of interest-based analysis with the easy-Z score imaging system. Multivariable logistic regression analysis with the presence of DAT was used to create its prediction model.

Results

The whole brain analysis showed that preoperative CBF in the insula was lower in the DAT than in the non-DAT group (P<0.05, family-wise error correction). Decrease extent ratio in the insula of the DAT group (17.6±11.5%) was also greater relative to that of the non-DAT group (7.0±11.3%) in the region of interest-based analysis (P = 0.007). A model that included preoperative CBF in the insula and conventional indicators (frailty index, short physical performance battery and mini-mental state examination) showed the best predictive power for DAT (AUC 0.882).

Conclusions

These results suggest that preoperative CBF in the insula is associated with DAT and may be useful for its prediction.

Stroke, Seizures, Hallucinations and Postoperative Delirium as Neurological Complications after Cardiac Surgery and Percutaneous Valve Replacement

(1) Background: Neurological complications such as acute ischemic stroke or postoperative delirium are frequent after cardiac surgery or percutaneous valve replacement. This study aimed to identify corresponding risk factors. (2) Methods: 297 patients with percutaneous valve replacement or cardiac surgery were postoperatively screened for neurological complications such as delirium, stroke, seizures and hallucinations twice daily for three days. Pre- and perioperative risk factors were evaluated in a multivariate model. (3) Results: Neurological complications occurred in 43.8% (n = 130) as composed of delirium (43.43%, n = 129), stroke (2.7%, n = 8), seizures (1.35%, n = 4) and real hallucinations (3.36%, n = 10). Multiple logistic regression revealed an association of neurological complications with lower Montreal Cognitive Assessment scores (Exp(B) 2.042; 95% CI, 1.183−3.525, p = 0.010), older age (Exp(B) 1.071; 95% CI, 1.036−1.107, p < 0.001), red blood cell transfusions until postoperative day 3 (Exp(B) 1.157; 95% CI, 1.030−1.300, p = 0.014), history of heart failure (Exp(B) 1.985; 95% CI, 1.130−3.487, p = 0.017) and increased CRP levels (Exp(B) 1.004; 95% CI, 1.000−1.008, p = 0.037). (4) Conclusions: Postoperative delirium remains a frequent complication after cardiac surgery, while stroke and seizures occur rarely. A preoperative risk profile including older age, history of heart failure and cognitive impairment was identified for a complicated postoperative course. However, the impact of an intense inflammatory response must not be neglected.

Psychogenic coma after general anesthesia with remimazolam and remifentanil -a case report

BACKGROUND

Delayed emergence from general anesthesia is associated with life-threatening conditions with pharmacological, neurological, metabolic, and rarely, psychiatric causes. This case report was presented to report psychogenic coma after recovery from anesthesia with remimazolam and remifentanil.

CASE

An elderly woman was unresponsive after recovery from anesthesia with remimazolam and remifentanil. Physical examination, laboratory testing, and radiographic imaging did not reveal any obvious organic causes. Pharmacological or metabolic abnormalities were not found. Absence of those causes strongly suggests that prolonged unconsciousness is related to psychiatric origin. The patient spontaneously regained consciousness after 48 h without any neurological complications.

CONCLUSIONS

Anesthesiologists should be aware of the possibility of psychogenic coma for patients with unexplained delay in emergence from anesthesia after the exclusion of other causes.

Quantitative Electroencephalographic Markers of Delirium in the Pediatric Intensive Care Unit: Insights From a Heterogenous Convenience Sample

OBJECTIVE

Little is known about the underlying neurophysiology of pediatric delirium. In adult patients, the sensitivity of EEG to clinical symptoms of delirium has been noted, with a slowing of background activity (alpha) and an increase in slow-wave activity (delta-theta). In this pilot study, the authors extended this investigation to a pediatric cohort.

METHODS

In a convenience sample, 23 critically ill children were screened for delirium, using the Cornell Assessment for Pediatric Delirium (CAPD), every 12 hours throughout their pediatric intensive care unit stay as part of standard intensive care unit procedure, and EEGs were performed as part of their clinical care. After hospital discharge, EEGs were reviewed using quantitative analysis, and the maximum delta-alpha ratio (DAR; eyes closed) was derived for each 12-hour period. DAR values were compared between delirious and nondelirious episodes, and the linear relationship between DAR and CAPD was assessed.

RESULTS

Higher DARs were associated with episodes of delirium. The DAR also positively correlated with CAPD assessments, with higher DARs relating to higher delirium scores.

CONCLUSIONS

Future prospective studies may further investigate this relationship in a more homogeneous and larger sample, and the DAR should be considered to track delirium and assess the effectiveness of therapeutic interventions.

Case Report: Triphasic Waves in a 9-Year-Old Girl With Anti-NMDAR Encephalitis

BACKGROUND

Triphasic waves (TWs) are mainly described in association with metabolic encephalopathy, especially hepatic encephalopathy. Now, as different conditions including non-metabolic and structural abnormalities have been reported to be associated with TWs, the presence of TWs becomes a non-specific finding for metabolic encephalopathy.

CASE PRESENTATION

We report the first case of anti-NMDAR encephalitis in a 9-year-old girl presenting with TWs on EEG. The TWs background EEG lasted for about 12 h on the 40th day of the disease course. No epileptic wave was found during a series of EEG examinations. The child was discharged from the hospital and no neurological sequelae remained after a six-month follow-up.

CONCLUSIONS

TWs are not specific to metabolic encephalopathy, but can also occur in children with autoimmune encephalitis. This case achieved a good prognosis after the early initiation of immunotherapy.

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

Supplemental Digital Content is available in the text.

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

Delirium associated with buprenorphine use in cardiac surgery: A retrospective cohort study

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Results:

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Postoperative delirium and neurocognitive disorders

PURPOSE OF REVIEW

Postoperative neurocognitive disorders (NCD) are significant causes of morbidity and mortality. In this paper, we will review our understanding and potential management of postoperative NCD.

RECENT FINDINGS

Postoperative delirium, delayed neurocognitive recovery and postoperative cognitive dysfunction (POCD) are recognized as a part of the continuous spectrum of postoperative NCD. Although the pathophysiology is still poorly understood, there is renewed focus on improving neurocognitive outcomes of aging surgical population. Novel methods of neurocognitive screening are developed and research in the prevention and management of NCD has gained traction.

SUMMARY

A spectrum of NCD exists in surgical patients ranging from postoperative delirium, delayed neurocognitive recovery, and POCD. Identification of patients at-risk for developing NCD can help target appropriate perioperative intervention. Also, specialized care teams and the implementation of standardized protocols are crucial for the successful management perioperative NCD. Finally, large, randomized, multicenter studies are needed to confirm benefits of preventive and treatment strategies.

Cerebral monitoring in surgical ICU patients

PURPOSE OF REVIEW

To give an overview of cerebral monitoring techniques for surgical ICU patients.

RECENT FINDINGS

As the burden of postsurgical neurological and neurocognitive complications becomes increasingly recognized, cerebral monitoring in the surgical ICU might gain a relevant role in detecting and possibly preventing adverse outcomes. However, identifying neurological alterations in surgical ICU patients, who are often sedated and mechanically ventilated, can be challenging. Various noninvasive and invasive techniques are available for cerebral monitoring, providing an assessment of cortical electrical activity, cerebral oxygenation, blood flow autoregulation, intracranial pressure, and cerebral metabolism. These techniques can be used for the diagnosis of subclinical seizures, the assessment of sedation depth and delirium, the detection of an impaired cerebral blood flow, and the diagnosis of neurosurgical complications.

SUMMARY

Cerebral monitoring can be a valuable tool in the early detection of adverse outcomes in surgical ICU patients, but the evidence is limited, and clear clinical indications are still lacking.

Thoracic Paravertebral Block Ameliorates Postoperative Delirium in Geriatric Patients

OBJECTIVES

 Thoracic surgery often causes postoperative delirium (POD) in geriatric patients. This study aimed to explore the effect of ultrasound-guided continuous thoracic paravertebral block (UG-TPVB) on POD in geriatric patients undergoing pulmonary resection.

METHODS

 Total 128 patients who underwent pulmonary resection were randomly allocated to either the conventional patient-controlled analgesia (PCA) group or the UG-TPVB group (n = 64 per group). The consumption of opioid agents (propofol and remifentanil), postoperative hospital stay, postoperative pulmonary atelectasis, postoperative nausea/vomiting, and postoperative itchiness were recorded. The diagnosis of delirium was dependent on the Nursing Delirium Screening Scale. The postoperative pain was assessed by visual analogue scale (VAS) score. The serum levels of interleukin (IL)-1β, IL-6, and tumor necrosis factor-α were used to evaluate the postoperative neuroinflammation.

RESULTS

 The consumption of propofol and remifentanil, postoperative hospital stay, postoperative pulmonary atelectasis, postoperative nausea/vomiting, and postoperative itchiness in the UG-TPVB group were lower than that in the PCA group. Compared with the PCA group, the prevalence of POD was decreased in the UG-TPVB group. In addition, use of UG-TPVB not only reduced postoperative pain (VAS score) but also decreased postoperative neuroinflammation compared with PCA in geriatric patients undergoing pulmonary resection.

CONCLUSIONS

 This study determined the benefits of UG-TPVB over PCA, providing an effectiveness approach to alleviate POD in geriatric patients undergoing pulmonary resection.

Electroencephalography of mechanically ventilated patients at high risk of delirium

Objective

Neurophysiological exploration of ICU delirium is limited. Here, we examined EEG characteristics of medical‐surgical critically ill patients with new‐onset altered consciousness state at high risk for ICU delirium.

Materials and methods

Pre‐planned analysis of non‐neurological mechanically ventilated medical‐surgical ICU subjects, who underwent a prospective multicenter randomized, controlled EEG study (NCT03129438, April 2017–November 2018). EEG characteristics, according to the 2012 ACNS nomenclature, included background activity, rhythmic periodic patterns/epileptic activity, amplitude, frequency, stimulus‐induced discharges, triphasic waves, reactivity, and NREM sleep. We explored EEG findings in delirious versus non‐delirious patients, specifically focusing on the presence of burst‐suppression and rhythmic periodic patterns (ictal‐interictal continuum), and ictal activity.

Results

We analyzed 91 patients (median age, 66 years) who underwent EEG because of new‐onset altered consciousness state at a median 5 days from admission; 42 patients developed delirium (46%). Burst‐suppression (10 vs 0%, p = .02), rhythmic/periodic patterns (43% vs 22%, p = .03) and epileptiform activity (7 vs 0%, p = .05) were more frequent in delirious versus non‐delirious patients. The presence of at least one of these abnormal EEG findings (32/91 patients; 35%) was associated with a significant increase in the likelihood of delirium (42 vs 15%, p = .006). Cumulative dose of sedatives and analgesics, as well as all other EEG characteristics, did not differ significantly between the two groups.

Conclusion

In mechanically ventilated non‐neurological critically ill patients with new‐onset alteration of consciousness, EEG showing burst‐suppression, rhythmic or periodic patterns, or seizures/status epilepticus indicate an increased risk of ICU delirium.

Evaluation of point-of-care thumb-size bispectral electroencephalography device to quantify delirium severity and predict mortality

BACKGROUND

We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes.

AIMS

To improve the BSEEG method by introducing a new EEG device.

METHOD

In a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed.

RESULTS

We enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality.

CONCLUSIONS

We confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

Biomarkers in delirium: A systematic review

BACKGROUND

Delirium is a common neuropsychiatric disorder associated with prolonged hospital stays, and increased morbidity and mortality. Diagnosis is frequently missed due to varying disease presentation and lack of standardized testing. We examined biomarkers as diagnostic or prognostic indicators of delirium, and provide a rational basis for future studies.

METHOD

Systematic review of literature published between Jan 2000 and June 2019. Searches included: PubMed; Web of Science; CINAHL; EMBASE; COCHRANE and Medline. Additional studies were identified by searching bibliographies of eligible articles.

RESULTS

2082 relevant papers were identified from all sources. Seventy-three met the inclusion criteria, all of which were observational. These assessed a range of fourteen biomarkers. All papers included were in the English language. Assessment methods varied between studies, including: DSM criteria; Confusion Assessment Method (CAM) or CAM-Intensive Care Unit (ICU). Delirium severity was measured using the Delirium Rating Scale (DRS). Delirium was secondary to post-operative dysfunction or acute medical conditions.

CONCLUSION

Evidence does not currently support the use of any one biomarker. However, certain markers were associated with promising results and may warrant evaluation in future studies. Heterogeneity across study methods may have contributed to inconclusive results, and more clarity may arise from standardization of methods of clinical assessment. Adjusting for comorbidities may improve understanding of the pathophysiology of delirium, in particular the role of confounders such as inflammation, cognitive disorders and surgical trauma. Future research may also benefit from inclusion of other diagnostic modalities such as EEG as well as analysis of genetic or epigenetic factors.

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.

The effect of foot reflexology massage on delirium and sleep quality following cardiac surgery: A randomized clinical trial

BACKGROUND

Delirium is the most common neurologic disorder after cardiac surgery and affects both short and long-term outcomes. This study was conducted to evaluate the effect of foot reflexology massage on the incidence of delirium and sleep quality in patients undergoing cardiac surgery.

METHODS

In this randomized clinical trial, 60 patients who were candidates for CABG surgery were randomly assigned into two equal groups (n = 30); intervention and control groups. In the intervention group, foot reflexology massage was done on each foot for 15 min, for two consecutive days. Delirium observation screening scale, the Richard Campbell sleep questionnaire (RSCQ), and pain intensity using VAS were compared.

RESULTS

in the second postoperative day, delirium was observed in 8 (26.7 %) and 7 (23.3 %) of patients in the intervention and control groups, respectively (p > 0.05). The measured odds ratio for the effect of massage on delirium is 0.83 (95 %CI 0.71-2.69, p = 0.76). The difference in RSCQ scores was not significant between groups of intervention and control (68.32 ± 10.41 VS. 62.80 ± 11.86, P = 0.06). The pain intensity was lower in the intervention group (P < 0.001).

CONCLUSION

Foot reflexology was not effective in reducing delirium and improving the sleep quality, but the pain intensity was decreased. It seems that the precise pathology and predicting model of delirium should be identified, and appropriate interventions should be planned accordingly.

Consciousness among delta waves: a paradox?

A common observation in EEG research is that consciousness vanishes with the appearance of delta (1 - 4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are very frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalised epileptic seizures, and disorders of consciousness such as coma and vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the "down states" or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and nonconvulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalogram or MEG signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.

Effects of general versus regional anaesthesia on circadian melatonin rhythm and its association with postoperative delirium in elderly patients undergoing hip fracture surgery: study protocol for a prospective cohort clinical trial

INTRODUCTION

Postoperative delirium (POD) is a common neurological complication after hip fracture surgery and is associated with high morbidity and mortality in elderly patients. Although the specific mechanism of POD remains unclear, circadian rhythm disruptions have recently drawn increased attention. To date, only limited postoperative time points of plasma melatonin level measurements were recorded in previous studies, and such data cannot represent a comprehensive melatonin rhythm. The process of anaesthesia (either general anaesthesia (GA) or regional anaesthesia (RA)) is known to influence the melatonin rhythm. However, how these two anaesthesia methods differently affect the postoperative melatonin rhythm is still unknown. Therefore, we hypothesise that RA may attenuate the disruption of the melatonin rhythm, which might decrease the incidence of POD in elderly patients undergoing hip surgery.

METHODS AND ANALYSIS

In this prospective cohort clinical trial, 138 patients scheduled for hip fracture surgery will be divided into two groups to receive either GA or RA. The primary aim is to compare the circadian rhythm of melatonin secretion between the two groups and explore its association with the incidence of POD.

ETHICS AND DISSEMINATION

The study has been approved by the Medical Science Research Ethics Committees of Beijing Jishuitan Hospital (JLKS201901-04). The results of the study will be published in peer-reviewed international journals.

TRIAL REGISTRATION NUMBER

ChiCTR1900027393.

Cortical Oscillations and Connectivity During Postoperative Recovery

BACKGROUND

The objective of this study was to test whether postoperative electroencephalographic (EEG) biomarkers, parietal alpha power and frontal-parietal connectivity, were associated with measures of clinical recovery in adult surgical patients.

METHODS

This is a secondary analysis of a prospective cohort study that analyzed intraoperative connectivity patterns in adult surgical patients (N=53). Wireless, whole-scalp EEG data were collected in the postanesthesia care unit and assessed for relevance to clinical and neurocognitive recovery. Parietal alpha power and frontal-parietal connectivity (estimated by weighted phase lag index) were tested for associations with postanesthesia care unit discharge readiness and University of Michigan Sedation Scale scores upon postoperative admission. Bivariable correlation and regression models were constructed to test for unadjusted associations, then multivariable regression models were constructed to adjust for confounding.

RESULTS

Postoperative EEG patterns were characterized by a predominance of alpha parietal power and frontal-parietal connectivity. Neither relative parietal alpha power (% alpha, -0.25; 95% confidence interval [CI], -1.41 to 0.90; P=0.657) nor alpha frontal-parietal connectivity (weighted phase lag index, -82; 95% CI, -237 to 73; P=0.287) were associated with time until postanesthesia discharge criteria were met. Furthermore, neither alpha power (-0.03; 95% CI, -0.07 to 0.01; P=0.206) nor alpha frontal-parietal connectivity (-4.2; 95% CI, -11 to 2.6; P=0.226) were associated with sedation scores upon initial assessment.

CONCLUSIONS

In a pragmatic study investigating clinically relevant endpoints of postoperative recovery, we found no correlation with surrogate measures of brain neurodynamics. These data contribute to the overall impetus of developing anesthetic-invariant and generalizable markers of brain recovery.

High-voltage, diffuse delta rhythms coincide with wakeful consciousness and complexity in Angelman syndrome

Abundant evidence from slow wave sleep, anesthesia, coma, and epileptic seizures links high-voltage, slow electroencephalogram (EEG) activity to loss of consciousness. This well-established correlation is challenged by the observation that children with Angelman syndrome (AS), while fully awake and displaying volitional behavior, display a hypersynchronous delta (1–4 Hz) frequency EEG phenotype typical of unconsciousness. Because the trough of the delta oscillation is associated with down-states in which cortical neurons are silenced, the presence of volitional behavior and wakefulness in AS amidst diffuse delta rhythms presents a paradox. Moreover, high-voltage, slow EEG activity is generally assumed to lack complexity, yet many theories view functional brain complexity as necessary for consciousness. Here, we use abnormal cortical dynamics in AS to assess whether EEG complexity may scale with the relative level of consciousness despite a background of hypersynchronous delta activity. As characterized by multiscale metrics, EEGs from 35 children with AS feature significantly greater complexity during wakefulness compared with sleep, even when comparing the most pathological segments of wakeful EEG to the segments of sleep EEG least likely to contain conscious mentation and when factoring out delta power differences across states. These findings (i) warn against reverse inferring an absence of consciousness solely on the basis of high-amplitude EEG delta oscillations, (ii) corroborate rare observations of preserved consciousness under hypersynchronization in other conditions, (iii) identify biomarkers of consciousness that have been validated under conditions of abnormal cortical dynamics, and (iv) lend credence to theories linking consciousness with complexity.

Delirium Screening in Neurocritical Care and Stroke Unit Patients: A Pilot Study on the Influence of Neurological Deficits on CAM-ICU and ICDSC Outcome

BACKGROUND/OBJECTIVE

Delirium is a common complication in critically ill patients with a negative impact on hospital length of stay, morbidity, and mortality. Little is known on how neurological deficits affect the outcome of commonly used delirium screening tools such as the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the Intensive Care Delirium Screening Checklist (ICDSC) in neurocritical care patients.

METHODS

Over a period of 1 month, all patients admitted to a neurocritical care and stroke unit at a single academic center were prospectively screened for delirium using both CAM-ICU and ICDSC. Tool-based delirium screening was compared with delirium evaluation by the treating clinical team. Additionally, ICD-10 delirium criteria were assessed.

RESULTS

One hundred twenty-three patients with a total of 644 daily screenings were included. Twenty-three patients (18.7%) were diagnosed with delirium according to the clinical evaluation. Delirium incidence amounted to 23.6% (CAM-ICU) and 26.8% (ICDSC). Sensitivity and specificity of both screening tools were 66.9% and 93.3% for CAM-ICU and 69.9% and 93.9% for ICDSC, respectively. Patients identified with delirium by either CAM-ICU or ICDSC presented a higher proportion of neurological deficits such as impaired consciousness, expressive aphasia, impaired language comprehension, and hemineglect. Subsequently, generalized estimating equations identified a significant association between impaired consciousness (as indexed by Richmond Agitation and Sedation Scale) and a positive delirium assessment with both CAM-ICU and ICDSC, while impaired language comprehension and hemineglect were only associated with a positive CAM-ICU result.

CONCLUSIONS

A positive delirium screening with both CAM-ICU and ICDSC in neurocritical care and stroke unit patients was found to be significantly associated with the presence of neurological deficits. These findings underline the need for a more specific delirium screening tool in neurocritical care patients.

The Effects of Transcranial Direct Current Stimulation on the Cognitive and Behavioral Changes After Electrode Implantation Surgery in Rats

Postoperative delirium can lead to increased morbidity and mortality, and may even be a potentially life-threatening clinical syndrome. However, the neural mechanism underlying this condition has not been fully understood and there is little knowledge regarding potential preventive strategies. To date, investigation of transcranial direct current stimulation (tDCS) for the relief of symptoms caused by neuropsychiatric disorders and the enhancement of cognitive performance has led to promising results. In this study, we demonstrated that tDCS has a possible effect on the fast recovery from delirium in rats after microelectrode implant surgery, as demonstrated by postoperative behavior and neurophysiology compared with sham stimulation. This is the first study to describe the possible effects of tDCS for the fast recovery from delirium based on the study of both electroencephalography and behavioral changes. Postoperative rats showed decreased attention, which is the core symptom of delirium. However, anodal tDCS over the right frontal area immediately after surgery exhibited positive effects on acute attentional deficit. It was found that relative power of theta was lower in the tDCS group than in the sham group after surgery, suggesting that the decrease might be the underlying reason for the positive effects of tDCS. Connectivity analysis revealed that tDCS could modulate effective connectivity and synchronization of brain activity among different brain areas, including the frontal cortex, parietal cortex, and thalamus. It was concluded that anodal tDCS on the right frontal regions may have the potential to help patients recover quickly from delirium.

Delirium is associated with frequency band specific dysconnectivity in intrinsic connectivity networks: preliminary evidence from a large retrospective pilot case-control study

Background

Pathophysiological concepts in delirium are not sufficient to define objective biomarkers suited to improve clinical approaches. Advances in neuroimaging have revalued electroencephalography (EEG) as a tool to assess oscillatory network activity in neuropsychiatric disease. Yet, research in the field is limited to small populations and largely confined to postoperative delirium, which impedes generalizability of findings and planning of prospective studies in other populations. This study aimed to assess effect sizes of connectivity measures in a large mixed population to demonstrate that there are measurable EEG differences between delirium and control patients.

Methods

This retrospective pilot study investigated EEG measures as biomarkers in delirium using a case-control design including patients diagnosed with delirium (DSM-5 criteria) and age-/gender-matched controls drawn from a database of 9980 patients (n = 129 and 414, respectively). Assessors were not blinded for groups. Power spectra and connectivity estimates, using the weighted phase log index, of continuous EEG data were compared between conditions. Alterations of information flow through nodes of intrinsic connectivity networks (ICN; default mode, salience, and executive control network) were evaluated in source space using betweenness centrality. This was done frequency specific and network nodes were defined by the multimodal human cerebral cortex parcellation based on human connectome project data.

Results

Delirium and control patients exhibited distinct EEG power, connectivity, and network characteristics (F_(72,540) = 70.3, p < .001; F_(493,1079) = 2.69, p < .001; and F_(718,2159) = 1.14, p = .007, respectively). Connectivity analyses revealed global alpha and regional beta band disconnectivity that was accompanied by theta band hyperconnectivity in delirious patients. Source and network analyses yielded that these changes are not specific to single intrinsic connectivity networks but affect multiple nodes of networks engaged in level of consciousness, attention, working memory, executive control, and salience detection. Effect sizes were medium to strong in this mixed population of delirious patients.

Conclusions

We quantified effect sizes for EEG connectivity and network analyses to be expected in delirium. This study implicates that theta band hyperconnectivity and alpha band disconnectivity may be essential mechanisms in the pathophysiology of delirium. Upcoming prospective studies will build upon these results and evaluate the clinical utility of identified EEG measures as therapeutic and prognostic biomarkers.

Electronic supplementary material

The online version of this article (10.1186/s40814-018-0388-z) contains supplementary material, which is available to authorized users.

Electroencephalogram dynamics during general anesthesia predict the later incidence and duration of burst-suppression during cardiopulmonary bypass

OBJECTIVE

Electroencephalogram burst-suppression during general anesthesia is associated with post-operative delirium (POD). Whether burst-suppression causes POD or merely reflects susceptibility to POD is unclear. We hypothesized decreased intraoperative alpha (8-12 Hz) and beta (13-33 Hz) power prior to the occurrence of burst-suppression in susceptible patients.

METHODS

We analyzed intraoperative electroencephalogram data of cardiac surgical patients undergoing cardiopulmonary bypass (CPB). We detected the incidence and duration of CPB burst-suppression with an automated burst-suppression detection algorithm. We analyzed EEG data with multitaper spectral estimation methods. We assessed associations between patient characteristics and burst-suppression using Binomial and Zero-inflated Poisson Regression Models.

RESULTS

We found significantly decreased alpha and beta power (7.8-22.95 Hz) in the CPB burst-suppression cohort. The odds ratio for the association between point estimates for alpha and beta power (7.8-22.95 Hz) and the incidence of burst-suppression was 0.88 (95% CI: 0.79-0.98). The incidence rate ratio for the association between point estimates for power between the alpha and beta range and the duration of burst-suppression was 0.89 (95% CI: 0.84-0.93).

CONCLUSION

Decreased intra-operative power within the alpha and beta range was associated with susceptibility to burst-suppression during CPB.

SIGNIFICANCE

This dynamic may be used to develop principled neurophysiological-based approaches to aid the preemptive identification and targeted care of POD vulnerable patients.

Neuroanesthesiology Update

We provide a synopsis of innovative research, recurring themes, and novel experimental findings pertinent to the care of neurosurgical patients and critically ill patients with neurological diseases. We cover the following broad topics: general neurosurgery, spine surgery, stroke, traumatic brain injury, monitoring, and anesthetic neurotoxicity.

Neuromonitoring in the ambulatory anesthesia setting: a pro-con discussion

PURPOSE OF REVIEW

Various neurologically focused monitoring modalities such as processed electroencephalography (pEEG), tissue/brain oxygenation monitors (SbO2), and even somatosensory evoked responses have been suggested as having the potential to improve the well tolerated and effective delivery of care in the setting of outpatient surgery. The present article will discuss the pros and cons of such monitors in this environment.

RECENT FINDINGS

There is a paucity of evidence from rigorous, well designed clinical trials demonstrating that the routine use of any neuromonitoring technique in an ambulatory surgery setting leads to meaningful cost savings or a reduction in morbidity or mortality.

SUMMARY

The use of advanced neuromonitoring techniques (primarily pEEG) may be considered reasonable in two instances: for the prevention of intraoperative awareness during the administration of total intravenous anesthesia coupled with the use of a neuromuscular blocking drug, and for the prevention of relative drug overdose (and possibly postoperative delirium) in the elderly.

An update on postoperative delirium: Clinical features, neuropathogenesis, and perioperative management

PURPOSE OF REVIEW

We present a focused review on postoperative delirium for anesthesiologists, encompassing clinical features, neuropathogenesis, and clinical identification and management strategies based on risk factors and current delirium treatments.

RECENT FINDINGS

The literature on postoperative delirium is dominated by non-experimental studies. We review delirium phenotypes, diagnostic criteria, and present standard nomenclature based on current literature. Disruption of cortical integration of complex information (CICI) may provide a framework to understand the neuropathogenesis of postoperative delirium, as well as risk factors and clinical modifiers in the perioperative period. We further divide risk factors into patient factors, surgical factors, and medical/pharmacological factors, and present specific considerations for each in the preoperative, intraoperative, and postoperative periods.

SUMMARY

Postoperative delirium is prevalent, poorly understood, and often missed with current screening techniques. Proper identification of risk factors is useful for perioperative interventions and can help tailor patient-specific management strategies.