Neurophysiology of Surgical Procedures for Repair of The Aortic Arch

Effects of EEG burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients: A randomized clinical trial

BACKGROUND

This randomized clinical trial determined the effects of electroencephalographic burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients.

METHODS

The patients were placed into burst suppression (BS) and non-burst suppression (NBS) groups. All patients were under bispectral index monitoring of an etomidate target-controlled infusion for anesthesia induction and intraoperative combination sevoflurane and remifentanil for anesthesia maintenance. The cerebral oxygen extraction ratio (CERO2), jugular bulb venous saturation (SjvO2), and difference in arteriovenous oxygen (Da-jvO2) were measured at T0, T1, and T2. One day before surgery, and 1, 3, and 7 days after surgery, postoperative cognitive dysfunction was assessed using the mini-mental state examination (MMSE).

RESULTS

Compared with T0, the Da-jvO2 and CERO2 values were decreased, and SjvO2 was increased in the 2 groups at T1 and T2 (P < .05). There was no statistical difference in the SjvO2, Da-jvO2, and CERO2 values between T1 and T2. Compared with the NBS group, the SjvO2 value increased, and the Da-jvO2 and CERO2 values decreased at T1 and T2 in the BS group (P < .05). The MMSE scores on the 1st and 3rd days postoperatively were significantly lower in the 2 groups compared to the preoperative MMSE scores (P < .05). The MMSE scores of the NBS group were higher than the BS group on the 1st and 3rd days postoperatively (P < .05).

CONCLUSION

In elderly patients undergoing surgery, intraoperative BS significantly reduced cerebral oxygen metabolism, which temporarily affected postoperative neurocognitive function.

Revealing the Cortical Glutamatergic Neural Activity During Burst Suppression by Simultaneous wide Field Calcium Imaging and Electroencephalography in Mice

Burst suppression (BS) is an electroencephalogram (EEG) pattern in which signals alternates between high-amplitude slow waves (burst waves) and nearly flat low-amplitude waves (suppression waves). In this study, we used wide-field (8.32 mm × 8.32 mm) fluorescent calcium imaging to record the activity of glutamatergic neurons in the parietal and occipital cortex, in conjunction with EEG recordings under BS induced by different anesthetics (sevoflurane, isoflurane, and propofol), to investigate the spatiotemporal pattern of neural activity under BS. The calcium signal of all observed cortices was decreased during the phase of EEG suppression. However, during the phase of EEG burst, the calcium signal in areas of the medial cortex, such as the secondary motor and retrosplenial area, was excited, whereas the signal in areas of the lateral cortex, such as the hindlimb cortex, forelimb cortex, barrel field, and primary visual area, was still suppressed or only weakly excited. Correlation analysis showed a strong correlation between the EEG signal and the calcium signal in the medial cortex under BS (except for propofol induced signals). As the burst-suppression ratio (BSR) increased, the regions with strong correlation coefficients became smaller, but strong correlation coefficients were still noted in the medial cortex. Taken together, our results reveal the landscape of cortical activity underlying BS.

Neuroprotective Strategies in Repair and Replacement of the Aortic Arch

Aortic arch surgery is a technical challenge, and cerebral protection during distal anastomosis is a continued topic of controversy and discussion. The physiologic effects of hypothermic arrest and adjunctive cerebral perfusion have yet to be fully defined, and the optimal strategies are still undetermined. This review highlights the historical context, physiological rationale, and clinical efficacy of various neuroprotective strategies during arch operations.

Neurophysiological Intraoperative Monitoring During Aortic Arch Surgery

Circulatory management during replacement of the aortic arch is complex and involves a period of circulatory arrest to provide a bloodless field during arch vessel anastomosis. To guard against ischemic brain injury, tissue metabolic demand is reduced by systemically cooling the patient prior to circulatory arrest. Neurophysiological intraoperative monitoring (NIOM) is often used during the course of these procedures to provide contemporaneous assessment of brain status to help direct circulatory management decisions and detect brain ischemia. In this review, we discuss the characteristics of electrocerebral activity through the process of cooling, circulatory arrest, and rewarming as depicted through commonly used NIOM modalities, including electroencephalography and peripheral nerve somatosensory-evoked potentials. Attention is directed toward the role NIOM has traditionally played during deep hypothermic circulatory arrest, where it is used to define the point of electrocerebral inactivity or maximal cerebral metabolic suppression prior to initiating circulatory arrest while also discussing the evolving utility of NIOM when systemic circulatory arrest is initiated at more moderate degrees of hypothermia in conjunction with regional brain perfusion. The use of cerebral tissue oximetry by near-infrared spectroscopy as an alternative NIOM modality during surgery of the aortic arch is addressed as well. Finally, special considerations for NIOM and the detection of spinal cord ischemia during hybrid aortic arch repair and emerging operative techniques are also discussed.

A Pharmacokinetics-Neural Mass Model (PK-NMM) for the Simulation of EEG Activity during Propofol Anesthesia

Modeling the effects of anesthetic drugs on brain activity is very helpful in understanding anesthesia mechanisms. The aim of this study was to set up a combined model to relate actual drug levels to EEG dynamics and behavioral states during propofol-induced anesthesia. We proposed a new combined theoretical model based on a pharmacokinetics (PK) model and a neural mass model (NMM), which we termed PK-NMM--with the aim of simulating electroencephalogram (EEG) activity during propofol-induced general anesthesia. The PK model was used to derive propofol effect-site drug concentrations (C(eff)) based on the actual drug infusion regimen. The NMM model took C(eff) as the control parameter to produce simulated EEG-like (sEEG) data. For comparison, we used real prefrontal EEG (rEEG) data of nine volunteers undergoing propofol anesthesia from a previous experiment. To see how well the sEEG could describe the dynamic changes of neural activity during anesthesia, the rEEG data and the sEEG data were compared with respect to: power-frequency plots; nonlinear exponent (permutation entropy (PE)); and bispectral SynchFastSlow (SFS) parameters. We found that the PK-NMM model was able to reproduce anesthesia EEG-like signals based on the estimated drug concentration and patients' condition. The frequency spectrum indicated that the frequency power peak of the sEEG moved towards the low frequency band as anesthesia deepened. Different anesthetic states could be differentiated by the PE index. The correlation coefficient of PE was 0.80 ± 0.13 (mean ± standard deviation) between rEEG and sEEG for all subjects. Additionally, SFS could track the depth of anesthesia and the SFS of rEEG and sEEG were highly correlated with a correlation coefficient of 0.77 ± 0.13. The PK-NMM model could simulate EEG activity and might be a useful tool for understanding the action of propofol on brain activity.

The human burst suppression electroencephalogram of deep hypothermia

OBJECTIVE

Deep hypothermia induces 'burst suppression' (BS), an electroencephalogram pattern with low-voltage 'suppressions' alternating with high-voltage 'bursts'. Current understanding of BS comes mainly from anesthesia studies, while hypothermia-induced BS has received little study. We set out to investigate the electroencephalogram changes induced by cooling the human brain through increasing depths of BS through isoelectricity.

METHODS

We recorded scalp electroencephalograms from eleven patients undergoing deep hypothermia during cardiac surgery with complete circulatory arrest, and analyzed these using methods of spectral analysis.

RESULTS

Within patients, the depth of BS systematically depends on the depth of hypothermia, though responses vary between patients except at temperature extremes. With decreasing temperature, burst lengths increase, and burst amplitudes and lengths decrease, while the spectral content of bursts remains constant.

CONCLUSIONS

These findings support an existing theoretical model in which the common mechanism of burst suppression across diverse etiologies is the cyclical diffuse depletion of metabolic resources, and suggest the new hypothesis of local micro-network dropout to explain decreasing burst amplitudes at lower temperatures.

SIGNIFICANCE

These results pave the way for accurate noninvasive tracking of brain metabolic state during surgical procedures under deep hypothermia, and suggest new testable predictions about the network mechanisms underlying burst suppression.

Association between intraoperative electroencephalographic suppression and postoperative mortality

BACKGROUND

Low bispectral index values frequently reflect EEG suppression and have been associated with postoperative mortality. This study investigated whether intraoperative EEG suppression was an independent predictor of 90 day postoperative mortality and explored risk factors for EEG suppression.

METHODS

This observational study included 2662 adults enrolled in the B-Unaware or BAG-RECALL trials. A cohort was defined with >5 cumulative minutes of EEG suppression, and 1:2 propensity-matched to a non-suppressed cohort (≤5 min suppression). We evaluated the association between EEG suppression and mortality using multivariable logistic regression, and examined risk factors for EEG suppression using zero-inflated mixed effects analysis.

RESULTS

Ninety day postoperative mortality was 3.9% overall, 6.3% in the suppressed cohort, and 3.0% in the non-suppressed cohort {odds ratio (OR) [95% confidence interval (CI)]=2.19 (1.48-3.26)}. After matching and multivariable adjustment, EEG suppression was not associated with mortality [OR (95% CI)=0.83 (0.55-1.25)]; however, the interaction between EEG suppression and mean arterial pressure (MAP) <55 mm Hg was [OR (95% CI)=2.96 (1.34-6.52)]. Risk factors for EEG suppression were older age, number of comorbidities, chronic obstructive pulmonary disease, and higher intraoperative doses of benzodiazepines, opioids, or volatile anaesthetics. EEG suppression was less likely in patients with cancer, preoperative alcohol, opioid or benzodiazepine consumption, and intraoperative nitrous oxide exposure.

CONCLUSIONS

Although EEG suppression was associated with increasing anaesthetic administration and comorbidities, the hypothesis that intraoperative EEG suppression is a predictor of postoperative mortality was only supported if it was coincident with low MAP.

CLINICAL TRIAL REGISTRATION

NCT00281489 and NCT00682825.

Burst suppression probability algorithms: state-space methods for tracking EEG burst suppression

OBJECTIVE

Burst suppression is an electroencephalogram pattern in which bursts of electrical activity alternate with an isoelectric state. This pattern is commonly seen in states of severely reduced brain activity such as profound general anesthesia, anoxic brain injuries, hypothermia and certain developmental disorders. Devising accurate, reliable ways to quantify burst suppression is an important clinical and research problem. Although thresholding and segmentation algorithms readily identify burst suppression periods, analysis algorithms require long intervals of data to characterize burst suppression at a given time and provide no framework for statistical inference.

APPROACH

We introduce the concept of the burst suppression probability (BSP) to define the brain's instantaneous propensity of being in the suppressed state. To conduct dynamic analyses of burst suppression we propose a state-space model in which the observation process is a binomial model and the state equation is a Gaussian random walk. We estimate the model using an approximate expectation maximization algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia and a patient during induction of controlled hypothermia.

MAIN RESULT

The BSP algorithms track burst suppression on a second-to-second time scale, and make possible formal statistical comparisons of burst suppression at different times.

SIGNIFICANCE

The state-space approach suggests a principled and informative way to analyze burst suppression that can be used to monitor, and eventually to control, the brain states of patients in the operating room and in the intensive care unit.

Neurophysiologic responses of peripheral nerve to repeated episodes of anoxia

OBJECTIVE

Determine the effects of serial episodes of anoxia in an in vitro peripheral nerve preparation.

METHODS

The nerve action potential (NAP) from rat sciatic nerve was recorded during 5 cycles of anoxia and reperfusion. Multiple NAP parameters were analyzed as well as stimulus response curves.

RESULTS

The amplitude of the NAP declined to half baseline in 865 s on the first cycle of anoxia and recovered to half baseline during recovery in 470 s. These times increased with successive cycles of anoxia. The current required to produce a half maximal NAP showed a variable initial decrease before increasing with anoxia. The paired-pulse response showed a decline at 2-3 ms interstimulus interval during anoxia but was less dependent of interstimulus interval during recovery. NAP amplitude and velocity decrease over successive cycles of anoxia at a rate greater than in the absence of anoxia.

CONCLUSIONS

The NAP declines slowly when peripheral nerve is exposed to anoxia but returns at least twice as quickly when re-exposed to oxygen. Short periods of anoxia produce long lasting changes in the nerve suggesting greater resistance to anoxia. With serial episodes of anoxia there is gradual NAP amplitude reduction and increase in duration and latency.

SIGNIFICANCE

Anoxic-preconditioning appears in isolated peripheral nerve.

A neurophysiological-metabolic model for burst suppression

Burst suppression is an electroencepholagram (EEG) pattern in which high-voltage activity alternates with isoelectric quiescence. It is characteristic of an inactivated brain and is commonly observed at deep levels of general anesthesia, hypothermia, and in pathological conditions such as coma and early infantile encephalopathy. We propose a unifying mechanism for burst suppression that accounts for all of these conditions. By constructing a biophysical computational model, we show how the prevailing features of burst suppression may arise through the interaction between neuronal dynamics and brain metabolism. In each condition, the model suggests that a decrease in cerebral metabolic rate, coupled with the stabilizing properties of ATP-gated potassium channels, leads to the characteristic epochs of suppression. Consequently, the model makes a number of specific predictions of experimental and clinical relevance.