Airway management of lingual tonsillar hypertrophy: A narrative review.

Lingual tonsillar hypertrophy is rarely identified on routine airway assessment but may cause difficulties in airway management. We conducted a narrative review of case reports of lingual tonsillar hypertrophy to examine associated patient factors, success rates of airway management techniques and complications. We searched the literature for anaesthetic management of cases with lingual tonsillar hypertrophy. We found 89 patients in various case reports, from which we derived 92 cases to analyse. 64% of cases were assessed as having a normal airway. Difficult and impossible face mask ventilation occurred in 29.6% and 1.4% of cases, respectively. Difficult intubation and failed intubation occurred in 89.1% and 21.7% of cases, respectively. Multiple attempts (up to six) at intubation were performed, with no successful intubation after the third attempt with direct laryngoscopy. Some 16.5% of patients were woken up and 4.3% required emergency front of neck access. Complications included oesophageal intubation (10.9%), bleeding (9.8%) and severe hypoxia (3.2%). Our findings show that severe cases of lingual hypertrophy may cause an unanticipated difficult airway and serious complications, including hypoxic brain damage and death. A robust airway strategy is required which includes limiting the number of attempts at laryngoscopy, and early priming and performance of emergency front of neck access if required. In patients with known severe lingual tonsillar hypertrophy, awake intubation should be considered.

Deconstructing delirium in the post anaesthesia care unit.

The course of neuro-cognitive recovery following anaesthesia and surgery is distinctive and poorly understood. Our objective was to identify patterns of neuro-cognitive recovery of the domains routinely assessed for delirium diagnosis in the post anaesthesia care unit (PACU) and to compare them to the cognitive recovery patterns observed in other studies; thereby aiding in the identification of pathological (high risk) patterns of recovery in the PACU. We also compared which of the currently available tests (3D-CAM, CAM-ICU, and NuDESC) is the best to use in PACU. This was a post hoc secondary analysis of data from the Alpha Max study which involved 200 patients aged over 60 years, scheduled for elective surgery under general anaesthesia lasting more than 2 h. These patients were assessed for delirium at 30 min following arrival in the PACU, if they were adequately arousable (Richmond Agitation Sedation Score ≥ -2). All tests for delirium diagnosis (3D-CAM, CAM-ICU, and NuDESC) and the sub-domains assessed were compared to understand temporal recovery of neurocognitive domains. These data were also analysed to determine the best predictor of PACU delirium. We found the incidence of PACU delirium was 35% (3D-CAM). Individual cognitive domains were affected differently. Few individuals had vigilance deficits (6.5%, n = 10 CAM-ICU) or disorganized thinking (19% CAM-ICU, 27.5% 3D-CAM), in contrast attention deficits were common (72%, n = 144) and most of these patients (89.5%, n = 129) were not sedated (RASS ≥ -2). CAM-ICU (27%) and NuDESC (52.8%) detected fewer cases of PACU delirium compared to 3D-CAM. In conclusion, return of neurocognitive function is a stepwise process; Vigilance and Disorganized Thinking are the earliest cognitive functions to return to baseline and lingering deficits in these domains could indicate an abnormal cognitive recovery. Attention deficits are relatively common at 30 min in the PACU even in individuals who appear to be awake. The 3D CAM is a robust test to check for delirium in the PACU.

Investigating critical flicker fusion frequency for monitoring gas narcosis in divers.

INTRODUCTION: Critical flicker fusion frequency (CFFF) has been used in various studies to measure the cognitive effects of gas mixtures at depth, sometimes with conflicting or apparently paradoxical results. This study aimed to evaluate a novel automatic CFFF method and investigate whether CFFF can be used to monitor gas-induced narcosis in divers. METHODS: Three hyperbaric chamber experiments were performed: 1) Automated and manual CFFF measurements during air breathing at 608 kPa (n = 16 subjects); 2) Manual CFFF measurements during air and heliox breathing at sea level (101.3 kPa) and 608 kPa (n = 12); 3) Manual CFFF measurements during oxygen breathing at sea level, 142 and 284 kPa (n = 10). All results were compared to breathing air at sea level. RESULTS: Only breathing oxygen at sea level, and at 284 kPa, caused a significant decrease in CFFF (2.5% and 2.6% respectively compared to breathing air at sea level. None of the other conditions showed a difference with sea level air breathing. CONCLUSIONS: CFFF did not significantly change in our experiments when breathing air at 608 kPa compared to air breathing at sea level pressure using both devices. Based on our results CFFF does not seem to be a sensitive tool for measuring gas narcosis in divers in our laboratory setting.

Pupillometry is not sensitive to gas narcosis in divers breathing hyperbaric air or normobaric nitrous oxide.

INTRODUCTION: Gas narcosis impairs divers when diving deeper. Pupillometry is sensitive to alcohol intoxication and it has been used in anaesthesia to assess nitrous oxide narcosis. It is a potential novel method to quantify narcosis in diving. The aim of this study was to evaluate pupillometry for objective measurement of narcosis during exposure to hyperbaric air or nitrous oxide. METHOD: Pupil size in 16 subjects was recorded directly at surface pressure and during air breathing at 608 kPa (equivalent to 50 metres' seawater depth) in a hyperbaric chamber. Another 12 subjects were exposed to nitrous oxide at end-tidal percentages of 20, 30 and 40% in random order at surface pressure. Pupil size and pupil light reflex were recorded at baseline and at each level of nitrous oxide exposure. RESULTS: Pupil size did not significantly change during exposure to hyperbaric air or nitrous oxide. The pupil light reflex, evaluated using percentage constriction and minimum diameter after exposure to a light stimulus, was affected significantly only during the highest nitrous oxide exposure - an end-tidal level of 40%. CONCLUSION: Pupillometry is insensitive to the narcotic effect of air at 608 kPa in the dry hyperbaric environment and to the effects of low dose nitrous oxide. Pupillometry is not suitable as a monitoring method for gas narcosis in diving.

An Introduction to Causal Diagrams for Anesthesiology Research.

Making good decisions in the era of Big Data requires a sophisticated approach to causality. We are acutely aware that association ≠ causation, yet untangling the two remains one of our greatest challenges. This realization has stimulated a Causal Revolution in epidemiology, and the lessons learned are highly relevant to anesthesia research. This article introduces readers to directed acyclic graphs; a cornerstone of modern causal inference techniques. These diagrams provide a robust framework to address sources of bias and discover causal effects. We use the topical question of whether anesthetic technique (total intravenous anesthesia vs. volatile) affects outcome after cancer surgery as a basis for a series of example directed acyclic graphs, which demonstrate how variables can be chosen to statistically control confounding and other sources of bias. We also illustrate how controlling for the wrong variables can introduce, rather than eliminate, bias; and how directed acyclic graphs can help us diagnose this problem.This is a rapidly evolving field, and we cover only the most basic elements. The true promise of these techniques is that it may become possible to make robust statements about causation from observational studies-without the expense and artificiality of randomized controlled trials.

Transient electroencephalographic alpha power loss during maintenance of general anaesthesia.

BACKGROUND: EEG activity in the extended alpha frequency range (7-17 Hz) during maintenance of general anaesthesia is primarily determined by effect-site concentrations of the hypnotic and analgesic drugs used. Intermittent alpha loss during surgery, unexplained by changes in anaesthetic or opioid concentrations, could represent arousal of the cortex as a result of increased surgical stimulation. METHODS: A generalised linear model was fitted to alpha power recorded from patients undergoing general anaesthesia from induction until waking using three explanatory variables: age-adjusted volatile anaesthetic effect-site concentration, and estimated effect-site propofol and opioid concentrations. Model residuals were decomposed into uncorrelated white noise and a fluctuating auto-correlated trend. Deviations of this local trend were classified as 'unexpected alpha dropout events'. To investigate whether these alpha dropouts might be explained by the effect of noxious stimulation, we related their occurrence to whether a patient was undergoing surgery involving the body cavity or not. RESULTS: Alpha power dropouts occurred in 73 of the 237 patients included in the final analysis (31%, median amplitude of -3.5 dB, duration=103 s). They showed a bimodal or broadly skewed distribution, being more probable soon after initial incision (32%), dropping to around 10% at 1 h, and then again increasing to >30% in operations lasting >3 h. Multivariate analysis showed that alpha dropouts were significantly associated with body cavity surgery (P=0.003) and with longer operations (P<0.001). CONCLUSIONS: A loss of alpha power, unexplained by changes in anaesthetic or opioid concentrations, is suggestive of thalamocortical depolarisation induced by body cavity noxious stimuli, and could provide a measure of nociception during surgery.

Non-sinusoidal waves in the EEG and their simulated effect on anaesthetic quantitative EEG monitors.

The effect of anaesthetic drugs on the cortex are commonly estimated from the electroencephalogram (EEG) by quantitative EEG monitors such as the Bispectral Index (BIS). These monitors use ratios of high to low frequency power which assumes that each neurological process contributes a unique frequency pattern. However, recent research of the effect of deep brain stimulation on EEG beta oscillations suggests that wave shape, a non-sinusoidal feature that is only measurable in the time-domain, can change the frequency 'signature' of a neurological rhythmical process by the inclusion or removal of harmonic frequencies. If wave shape variations are present in the EEG of anaesthetised patients, then quantitative EEG monitors likely overestimate the anaesthetic drug effect. The purpose of this paper is to investigate alpha-wave shape in the EEG of anaesthetised patients and demonstrate the effect of wave shape on the frequency ratios that are commonly utilised in the BIS quantitative EEG monitor. EEG data, demographic information, and surgery details were collected prospectively from 305 patients undergoing a general anaesthetic for elective surgery. Alpha-wave shape was categorised by triangularity of the EEG extrema, a measure of how peaked (towards a sawtooth wave) or flat (towards a square wave) the extremum was. The alpha-wave was then artificially modified to either a sawtooth wave or square wave, and BetaRatio and PowerFastSlow metrics calculated. Age was found to be the only significant predictor of alpha wave triangularity. The artificially modified square-alpha waves increased the power in the frequency spectrum at 26 Hz by 1-5 dB, and increased the BetaRatio by 0.7. The alpha-wave of anaesthetised patients contains non-sinusoidal components which likely impact depth of anaesthesia calculations.

Investigation of Slow-wave Activity Saturation during Surgical Anesthesia Reveals a Signature of Neural Inertia in Humans.

BACKGROUND: Previously, we showed experimentally that saturation of slow-wave activity provides a potentially individualized neurophysiologic endpoint for perception loss during anesthesia. Furthermore, it is clear that induction and emergence from anesthesia are not symmetrically reversible processes. The observed hysteresis is potentially underpinned by a neural inertia mechanism as proposed in animal studies. METHODS: In an advanced secondary analysis of 393 individual electroencephalographic data sets, we used slow-wave activity dose-response relationships to parameterize slow-wave activity saturation during induction and emergence from surgical anesthesia. We determined whether neural inertia exists in humans by comparing slow-wave activity dose responses on induction and emergence. RESULTS: Slow-wave activity saturation occurs for different anesthetics and when opioids and muscle relaxants are used during surgery. There was wide interpatient variability in the hypnotic concentrations required to achieve slow-wave activity saturation. Age negatively correlated with power at slow-wave activity saturation. On emergence, we observed abrupt decreases in slow-wave activity dose responses coincident with recovery of behavioral responsiveness in ~33% individuals. These patients are more likely to have lower power at slow-wave activity saturation, be older, and suffer from short-term confusion on emergence. CONCLUSIONS: Slow-wave activity saturation during surgical anesthesia implies that large variability in dosing is required to achieve a targeted potential loss of perception in individual patients. A signature for neural inertia in humans is the maintenance of slow-wave activity even in the presence of very-low hypnotic concentrations during emergence from anesthesia.

Electromyographic activation reveals cortical and sub-cortical dissociation during emergence from general anesthesia.

During emergence from anesthesia patients regain their muscle tone (EMG). In a typical population of surgical patients the actual volatile gas anesthetic concentrations in the brain (CeMAC) at which EMG activation occurs remains unknown, as is whether EMG activation at higher CeMACs is correlated with subsequent severe pain, or with cortical activation. Electroencephalographic (EEG) and EMG activity was recorded from the forehead of 273 patients emerging from general anesthesia following surgery. We determined CeMAC at time of EMG activation and at return of consciousness. Pain was assessed immediately after return of consciousness using an 11 point numerical rating scale. The onset of EMG activation during emergence was associated with neither discernible muscle movement nor with the presence of exogenous stimulation in half the patients. EMG activation could be modelled as two distinct processes; termed high- and low-CeMAC (occurring higher or lower than 0.07 CeMAC). Low-CeMAC activation was typically associated with simultaneous EMG activation and consciousness, and the presence of a laryngeal mask. In contrast, high-CeMAC EMG activation occurred independently of return of consciousness, and was not associated with severe post-operative pain, but was more common in the presence of an endotracheal tube. Patients emerging from general anesthesia with an endotracheal tube in place are more likely to have an EMG activation at higher CeMAC concentrations. These activations are not associated with subsequent high-pain, nor with cortical arousal, as evidenced by continuing delta waves in the EEG. Conversely, patients emerging from general anesthesia with a laryngeal mask demonstrate marked neural inertia-EMG activation occurs at a low CeMAC, and is closely temporally associated with return of consciousness.

Electroencephalographic variation during end maintenance and emergence from surgical anesthesia.

The re-establishment of conscious awareness after discontinuing general anesthesia has often been assumed to be the inverse of loss of consciousness. This is despite the obvious asymmetry in the initiation and termination of natural sleep. In order to characterize the restoration of consciousness after surgery, we recorded frontal electroencephalograph (EEG) from 100 patients in the operating room during maintenance and emergence from general anesthesia. We have defined, for the first time, 4 steady-state patterns of anesthetic maintenance based on the relative EEG power in the slow-wave (<14 Hz) frequency bands that dominate sleep and anesthesia. Unlike single-drug experiments performed in healthy volunteers, we found that surgical patients exhibited greater electroencephalographic heterogeneity while re-establishing conscious awareness after drug discontinuation. Moreover, these emergence patterns could be broadly grouped according to the duration and rapidity of transitions amongst these slow-wave dominated brain states that precede awakening. Most patients progressed gradually from a pattern characterized by strong peaks of delta (0.5-4 Hz) and alpha/spindle (8-14 Hz) power ('Slow-Wave Anesthesia') to a state marked by low delta-spindle power ('Non Slow-Wave Anesthesia') before awakening. However, 31% of patients transitioned abruptly from Slow-Wave Anesthesia to waking; they were also more likely to express pain in the post-operative period. Our results, based on sleep-staging classification, provide the first systematized nomenclature for tracking brain states under general anesthesia from maintenance to emergence, and suggest that these transitions may correlate with post-operative outcomes such as pain.

Emergence from general anesthesia and the sleep-manifold.

The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthesia and surgery varies starkly between patients. Can the EEG during this emergence period provide a means of estimating the underlying biological processes underpinning the return of consciousness? Can we use a model to infer these biological processes from the EEG patterns? A frontal EEG was recorded from 84 patients. Ten patients were chosen for state-space analysis. Five showed archetypal emergences; which consisted of a progressive decrease in alpha power and increase peak alpha frequency before return of responsiveness. The five non-archetypal emergences showed almost no spectral EEG changes (even as the volatile general anesthetic decreased) and then an abrupt return of responsiveness. We used Bayesian methods to estimate the likelihood of an EEG pattern corresponding to the position of the patient on a 2-dimensional manifold in a state space of excitatory connection strength vs. change in intrinsic resting neuronal membrane conductivity. We could thus visualize the trajectory of each patient in the state-space during their emergence period. The patients who followed an archetypal emergence displayed a very consistent pattern; consisting of progressive increase in conductivity, and a temporary period of increased connection strength before return of responsiveness. The non-archetypal emergence trajectories remained fixed in a region of phase space characterized by a relatively high conductivity and low connection strength throughout emergence. This unexpected progressive increase in conductivity during archetypal emergence may be due to an abating of the surgical stimulus during this period. Periods of high connection strength could represent forays into dissociated consciousness, but the model suggests all patients reposition near the fold in the state space to take advantage of bi-stable cortical dynamics before transitioning to consciousness.

Parameter selection in permutation entropy for an electroencephalographic measure of isoflurane anesthetic drug effect.

The permutation entropy (PE) of the electroencephalographic (EEG) signals has been proposed as a robust measure of anesthetic drug effect. The calculation of PE involves the somewhat arbitrary selection of embedding dimension (m) and lag (τ) parameters. Previous studies of PE include the analysis of EEG signals under sevoflurane or propofol anesthesia, where different parameter settings were determined using a number of different criteria. In this study we choose parameter values based on the quantitative performance, to quantify the effect of a wide range of concentrations of isoflurane on the EEG. We analyzed a set of previously published EEG data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane general anesthesia combined with epidural anesthesia. PE indices using a range of different parameter settings (m = 3-7, τ = 1-5) were calculated. These indices were evaluated as regards: the correlation coefficient (r) with isoflurane end-tidal concentration, the relationship with isoflurane effect-site concentration assessed by the coefficient of determination (R (2)) of the pharmacokinetic-pharmacodynamic models, and the prediction probability (PK). The embedding dimension (m) and lag (τ) have significant effect on the r values (Two-way repeated-measures ANOVA, p < 0.001). The proposed new permutation entropy index (NPEI) [a combination of PE(m = 3, τ = 2) and PE(m = 3, τ = 3)] performed best among all the parameter combinations, with r = 0.89(0.83-0.94), R (2) = 0.82(0.76-0.87), and PK = 0.80 (0.76-0.85). Further comparison with previously suggested PE measures, as well as other unrelated EEG measures, indicates the superiority of the NPEI. The PE can be utilized to indicate the dynamical changes of EEG signals under isoflurane anesthesia. In this study, the NPEI measure that combines the PE with m = 3, τ = 2 and that with m = 3, τ = 3 is optimal.

Unresponsiveness ≠ unconsciousness.

Consciousness is subjective experience. During both sleep and anesthesia, consciousness is common, evidenced by dreaming. A defining feature of dreaming is that, while conscious, we do not experience our environment; we are disconnected. Besides inducing behavioral unresponsiveness, a key goal of anesthesia is to prevent the experience of surgery (connected consciousness), by inducing either unconsciousness or disconnection of consciousness from the environment. Review of the isolated forearm technique demonstrates that consciousness, connectedness, and responsiveness uncouple during anesthesia; in clinical conditions, a median 37% of patients demonstrate connected consciousness. We describe potential neurobiological constructs that can explain this phenomenon: during light anesthesia the subcortical mechanisms subserving spontaneous behavioral responsiveness are disabled but information integration within the corticothalamic network continues to produce consciousness, and unperturbed norepinephrinergic signaling maintains connectedness. These concepts emphasize the need for developing anesthetic regimens and depth of anesthesia monitors that specifically target mechanisms of consciousness, connectedness, and responsiveness.

The effect of isoflurane anesthesia on the electroencephalogram assessed by harmonic wavelet bicoherence-based indices.

Bicoherence quantifies the degree of quadratic phase coupling among different frequency components within a signal. Previous studies, using Fourier-based methods of bicoherence calculation (FBIC), have demonstrated that electroencephalographic bicoherence can be related to the end-tidal concentration of inhaled anesthetic drugs. However, FBIC methods require excessively long sections of the encephalogram. This problem might be overcome by the use of wavelet-based methods. In this study, we compare FBIC and a recently developed wavelet bicoherence (WBIC) method as a tool to quantify the effect of isoflurane on the electroencephalogram. We analyzed a set of previously published electroencephalographic data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane general anesthesia combined with epidural anesthesia. Nine potential indices of the electroencephalographic anesthetic effect were obtained from the WBIC and FBIC techniques. The relationship between each index and end-tidal concentrations of isoflurane was evaluated using correlation coefficients (r), the inter-individual variations (CV) of index values, the coefficient of determination (R(2)) of the PKPD models and the prediction probability (P(K)). The WBIC-based indices tracked anesthetic effects better than the traditional FBIC-based ones. The DiagBic_En index (derived from the Shannon entropy of the diagonal bicoherence values) performed best [r = 0.79 (0.66-0.92), CV = 0.08 (0.05-0.12), R(2) = 0.80 (0.75-0.85), P(K) = 0.79 (0.75-0.83)]. Short data segments of ∼10-30 s were sufficient to reliably calculate the indices of WBIC. The wavelet-based bicoherence has advantages over the traditional Fourier-based bicoherence in analyzing volatile anesthetic effects on the electroencephalogram.