Brain fragility among middle-aged and elderly patients from electroencephalogram during induction of anaesthesia

The relationship between preoperative serum indirect bilirubin and postoperative delirium in geriatric patients undergoing joint replacement

BACKGROUND

Postoperative delirium (POD) is one of the most common complications in geriatric patients following surgery. Physiological concentration of bilirubin possesses anti-inflammatory, antioxidant and neuroprotective effects, which are important protective mechanisms against POD. This study aimed to explore the relationship between preoperative serum bilirubin and POD in geriatric patients undergoing joint replacement.

METHODS

Geriatric patients who underwent hip or knee joint replacement surgery under intrathecal anesthesia were included. These patients had American Society of Anesthesiologists (ASA) grades I to III. The patients with a history of psychiatric or neurological disorders, infectious diseases or sepsis, hemolytic anemia, liver diseases, performed general anesthesia or intrathecal anesthesia combined with general anesthesia, or insufficient surgical information were excluded. Patients' age, gender, weight, height, ASA classification, liver function and bilirubin within one week before surgery, preoperative Mini-Mental State Examination (MMSE) scores, surgical type, dosage of medications, intraoperative bleeding volume, postoperative average numeric rating scale (NRS) pain scores, the occurrence of POD and Delirium Rating Scale-Revised-98 (DRS-R-98) scores for POD were collected.

RESULTS

A total of 269 patients were eligible for inclusion in the study, with 23.05% (62/207) exhibiting POD. Patients with POD exhibited higher age and ASA classification, and had lower weight, serum total serum bilirubin (TBIL) and indirect bilirubin (IBIL) within one week before surgery, and preoperative MMSE scores (all p < 0.05). Univariate logistic regression analysis showed that the above variables were correlated with the occurrence of POD (all p < 0.05). Multivariate logistic regression analysis revealed that age was a risk factor (p < 0.001, OR = 1.14, 95% CI [1.07-1.21]), while weight (p = 0.041, OR = 0.96, 95% CI [0.92-0.99]), IBIL levels within one week before surgery (p = 0.012, OR = 0.65, 95% CI [0.47-0.91]) and preoperative MMSE scores (p < 0.001, OR = 0.84, 95% CI [0.78-0.91]) served as protective factors against the occurrence of POD. The serum IBIL concentration within one week before surgery was performed receiver operating characteristic (ROC) curve analysis. The estimated cutoff value for predicting the occurrence of POD was 6.65 μmol/L, and area under the curve (AUC) was 0.63. Patients with preoperative serum IBIL concentration below 6.65 μmol/L had a higher incidence of POD.

CONCLUSION

Patients with lower preoperative serum IBIL levels exhibited a higher incidence of POD in geriatric patients undergoing joint replacement. Low serum IBIL was a risk factor and a predictor for the occurrence of POD.

Electroencephalogram Biomarkers from Anesthesia Induction to Identify Vulnerable Patients at Risk for Postoperative Delirium

BACKGROUND

Postoperative delirium is a common complication in elderly patients undergoing anesthesia. Even though it is increasingly recognized as an important health issue, the early detection of patients at risk for postoperative delirium remains a challenge. This study aims to identify predictors of postoperative delirium by analyzing frontal electroencephalogram at propofol-induced loss of consciousness.

METHODS

This prospective, observational single-center study included patients older than 70 yr undergoing general anesthesia for a planned surgery. Frontal electroencephalogram was recorded on the day before surgery (baseline) and during anesthesia induction (1, 2, and 15 min after loss of consciousness). Postoperative patients were screened for postoperative delirium twice daily for 5 days. Spectral analysis was performed using the multitaper method. The electroencephalogram spectrum was decomposed in periodic and aperiodic (correlates to asynchronous spectrum wide activity) components. The aperiodic component is characterized by its offset (y intercept) and exponent (the slope of the curve). Computed electroencephalogram parameters were compared between patients who developed postoperative delirium and those who did not. Significant electroencephalogram parameters were included in a binary logistic regression analysis to predict vulnerability for postoperative delirium.

RESULTS

Of 151 patients, 50 (33%) developed postoperative delirium. At 1 min after loss of consciousness, postoperative delirium patients demonstrated decreased alpha (postoperative delirium: 0.3 μV2 [0.21 to 0.71], no postoperative delirium: 0.55 μV2 [0.36 to 0.74]; P = 0.019] and beta band power [postoperative delirium: 0.27 μV2 [0.12 to 0.38], no postoperative delirium: 0.38 μV2 [0.25 to 0.48]; P = 0.003) and lower spectral edge frequency (postoperative delirium: 10.45 Hz [5.65 to 15.04], no postoperative delirium: 14.56 Hz [9.51 to 16.65]; P = 0.01). At 15 min after loss of consciousness, postoperative delirium patients displayed a decreased aperiodic offset (postoperative delirium: 0.42 μV2 (0.11 to 0.69), no postoperative delirium: 0.62 μV2 [0.37 to 0.79]; P = 0.004). The logistic regression model predicting postoperative delirium vulnerability demonstrated an area under the curve of 0.73 (0.69 to 0.75).

CONCLUSIONS

The findings suggest that electroencephalogram markers obtained during loss of consciousness at anesthesia induction may serve as electroencephalogram-based biomarkers to identify at an early time patients at risk of developing postoperative delirium.

EDITOR’S PERSPECTIVE

Intraoperative Electroencephalography Alpha-Band Power Is a Better Proxy for Preoperative Low MoCA Under Propofol Compared With Sevoflurane

BACKGROUND

Preoperative abnormal cognitive status is a risk factor for postoperative complications yet remains underdiagnosed. During propofol general anesthesia, intraoperative electroencephalography (EEG) variables, such as alpha band power (α-BP), correlate with cognitive status. This relationship under sevoflurane is unclear. We investigated whether EEG biomarkers of poor cognitive status found under propofol could be extended to sevoflurane.

METHODS

In this monocentric prospective observational study, 106 patients with intraoperative EEG monitoring were included (propofol/sevoflurane = 55/51). We administered the Montreal Cognitive Assessment (MoCA) scale to identify abnormal cognition (low MoCA) 1 day before intervention. EEG variables included delta to beta frequency band powers. Results were adjusted to age and drug dosage. We assessed depth of anesthesia (DoA) using the spectral edge frequency (SEF 95 ) and maintained it within (8-13) Hz.

RESULTS

The difference in α-BP between low and normal MoCA patients was significantly larger among propofol patients (propofol: 4.3 ± 4.8 dB versus sevoflurane: 1.5 ± 3.4 dB, P = .022). SEF 95 and age were not statistically different between sevoflurane and propofol groups. After adjusting to age and dose, low α-BP was significantly associated with low MoCA under propofol (odds ratio [OR] [confidence interval {CI}] = 0.39 [0.16-0.94], P = .034), but not under sevoflurane, where theta-band power was significantly associated with low MoCA (OR [CI] = 0.31 [0.13-0.73], P = .007).

CONCLUSIONS

We suggest that intraoperative EEG biomarkers of abnormal cognition differ between propofol and sevoflurane under general anesthesia.

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.

Association of sleep and anaesthesia EEG biomarkers with preoperative MoCA score: A pilot study

INTRODUCTION

Preoperative cognitive impairments increase the risk of postoperative complications. The electroencephalogram (EEG) could provide information on cognitive vulnerability. The feasibility and clinical relevance of sleep EEG (EEG_sleep ) compared to intraoperative EEG (EEG_intraop ) in cognitive risk stratification remains to be explored. We investigated similarities between EEG_sleep and EEG_intraop vis-a-vis preoperative cognitive impairments.

METHODS

Pilot study including 27 patients (63 year old [53.5, 70.0]) to whom Montreal cognitive assessment (MoCA) and EEG_sleep were administered 1 day before a propofol-based general anaesthesia, in addition to EEG_intraop acquisition from depth-of-anaesthesia monitors. Sleep spindles on EEG_sleep and intraoperative alpha-band power on EEG_intraop were particularly explored.

RESULTS

In total, 11 (41%) patients had a MoCA <25 points. These patients had a significantly lower sleep spindle power on EEG_sleep (25 vs. 40 μv² /Hz, p = .035) and had a weaker intraoperative alpha-band power on EEG_intraop (85 vs. 150 μv² /Hz, p = .001) compared to patients with normal MoCA. Correlation between sleep spindle and intraoperative alpha-band power was positive and significant (r = 0.544, p = .003).

CONCLUSION

Preoperative cognitive impairment appears to be detectable by both EEG_sleep and EEG_intraop . Preoperative sleep EEG to assess perioperative cognitive risk is feasible but more data are needed to demonstrate its benefit compared to intraoperative EEG.

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

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