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Competing Interests: Conflicts of Interest, Funding: Please see DISCLOSURES at the end of this article.

Competing Interests: Conflicts of Interest, Funding: Please see DISCLOSURES at the end of this article.

Background: Anesthesia monitors and devices are usually controlled with some combination of dials, keypads, a keyboard, or a touch screen. Thus, anesthesiologists can operate their monitors only when they are physically close to them, and not otherwise task-loaded with sterile procedures such as line or block placement. Voice recognition technology has become commonplace and may offer advantages in anesthesia practice such as reducing surface contamination rates and allowing anesthesiologists to effect changes in monitoring and therapy when they would otherwise presently be unable to do so. We hypothesized that this technology is practicable and that anesthesiologists would consider it useful., Methods: A novel voice-driven prototype controller was designed for the GE Solar 8000M anesthesia patient monitor. The apparatus was implemented using a Raspberry Pi 4 single-board computer, an external conference audio device, a Google Cloud Speech-to-Text platform, and a modified Solar controller to effect commands. Fifty anesthesia providers tested the prototype. Evaluations and surveys were completed in a nonclinical environment to avoid any ethical or safety concerns regarding the use of the device in direct patient care. All anesthesiologists sampled were fluent English speakers; many with inflections from their first language or national origin, reflecting diversity in the population of practicing anesthesiologists., Results: The prototype was uniformly well-received by anesthesiologists. Ease-of-use, usefulness, and effectiveness were assessed on a Likert scale with means of 9.96, 7.22, and 8.48 of 10, respectively. No population cofactors were associated with these results. Advancing level of training (eg, nonattending versus attending) was not correlated with any preference. Accent of country or region was not correlated with any preference. Vocal pitch register did not correlate with any preference. Statistical analyses were performed with analysis of variance and the unpaired t -test., Conclusions: The use of voice recognition to control operating room monitors was well-received anesthesia providers. Additional commands are easily implemented on the prototype controller. No adverse relationship was found between acceptability and level of anesthesia experience, pitch of voice, or presence of accent. Voice recognition is a promising method of controlling anesthesia monitors and devices that could potentially increase usability and situational awareness in circumstances where the anesthesiologist is otherwise out-of-position or task-loaded., Competing Interests: Conflicts of Interest: See Disclosures at the end of the article., (Copyright © 2024 International Anesthesia Research Society.)

Competing Interests: Conflicts of Interest: See Disclosures at the end of the article.

In the emerging field of whole-brain imaging at single-cell resolution, which represents one of the new frontiers to investigate the link between brain activity and behavior, the nematode Caenorhabditis elegans offers one of the most characterized models for systems neuroscience. Whole-brain recordings consist of 3D time series of volumes that need to be processed to obtain neuronal traces. Current solutions for this task are either computationally demanding or limited to specific acquisition setups. Here, we propose See Elegans, a direct programming algorithm that combines different techniques for automatic neuron segmentation and tracking without the need for the RFP channel, and we compare it with other available algorithms. While outperforming them in most cases, our solution offers a novel method to guide the identification of a subset of head neurons based on position and activity. The built-in interface allows the user to follow and manually curate each of the processing steps. See Elegans is thus a simple-to-use interface aimed at speeding up the post-processing of volumetric calcium imaging recordings while maintaining a high level of accuracy and low computational demands. (Contact: enrico.lanza@iit.it)., Competing Interests: Viola Folli is an employee and scientific advisor of D-tails s.r.l. Valeria Lucente and Ilaria Cavallo are employees of D-tails s.r.l." However, this does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Lanza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Recent advances in neural networks have given rise to generative artificial intelligence, systems able to produce fluent responses to natural questions or attractive and even photorealistic images from text prompts. These systems were developed through new network architectures that permit massive computational resources to be applied efficiently to enormous data sets. First, this review examines autoencoder architecture and its derivatives the variational autoencoder and the U-Net in annotating and manipulating images and extracting salience. This architecture will be important for applications like automated x-ray interpretation or real-time highlighting of anatomy in ultrasound images. Second, this article examines the transformer architecture in the interpretation and generation of natural language, as it will be useful in producing automated summarization of medical records or performing initial patient screening. The author also applies the GPT-3.5 algorithm to example questions from the American Board of Anesthesiologists Basic Examination and find that, under surprisingly reasonable conditions, it correctly answers more than half the questions., (Copyright © 2024 American Society of Anesthesiologists. All Rights Reserved.)

Background: Suppression of behavioral and physical responses defines the anesthetized state. This is accompanied, in humans, by characteristic changes in electroencephalogram patterns. However, these measures reveal little about the neuron or circuit-level physiologic action of anesthetics nor how information is trafficked between neurons. This study assessed whether entropy-based metrics can differentiate between the awake and anesthetized state in Caenorhabditis elegans and characterize emergence from anesthesia at the level of interneuronal communication., Methods: Volumetric fluorescence imaging measured neuronal activity across a large portion of the C. elegans nervous system at cellular resolution during distinct states of isoflurane anesthesia, as well as during emergence from the anesthetized state. Using a generalized model of interneuronal communication, new entropy metrics were empirically derived that can distinguish the awake and anesthetized states., Results: This study derived three new entropy-based metrics that distinguish between stable awake and anesthetized states (isoflurane, n = 10) while possessing plausible physiologic interpretations. State decoupling is elevated in the anesthetized state (0%: 48.8 ± 3.50%; 4%: 66.9 ± 6.08%; 8%: 65.1 ± 5.16%; 0% vs. 4%, P < 0.001; 0% vs. 8%, P < 0.001), while internal predictability (0%: 46.0 ± 2.94%; 4%: 27.7 ± 5.13%; 8%: 30.5 ± 4.56%; 0% vs. 4%, P < 0.001; 0% vs. 8%, P < 0.001), and system consistency (0%: 2.64 ± 1.27%; 4%: 0.97 ± 1.38%; 8%: 1.14 ± 0.47%; 0% vs. 4%, P = 0.006; 0% vs. 8%, P = 0.015) are suppressed. These new metrics also resolve to baseline during gradual emergence of C. elegans from moderate levels of anesthesia to the awake state (n = 8). The results of this study show that early emergence from isoflurane anesthesia in C. elegans is characterized by the rapid resolution of an elevation in high frequency activity (n = 8, P = 0.032). The entropy-based metrics mutual information and transfer entropy, however, did not differentiate well between the awake and anesthetized states., Conclusions: Novel empirically derived entropy metrics better distinguish the awake and anesthetized states compared to extant metrics and reveal meaningful differences in information transfer characteristics between states., (Copyright © 2023 American Society of Anesthesiologists. All Rights Reserved.)

Competing Interests: Competing interests: Dr. Connor has consulted for Teleflex, LLC on issues regarding airway management and device design, and for General Biophysics, LLC on pharmacokinetics. These activities are unrelated to the material in this manuscript.

Background: BIS (a brand of processed electroencephalogram [EEG] depth-of-anesthesia monitor) scores have become interwoven into clinical anesthesia care and research. Yet, the algorithms used by such monitors remain proprietary. We do not actually know what we are measuring. If we knew, we could better understand the clinical prognostic significance of deviations in the score and make greater research advances in closed-loop control or avoiding postoperative cognitive dysfunction or juvenile neurological injury. In previous work, an A-2000 BIS monitor was forensically disassembled and its algorithms (the BIS Engine) retrieved as machine code. Development of an emulator allowed BIS scores to be calculated from arbitrary EEG data for the first time. We now address the fundamental questions of how these algorithms function and what they represent physiologically., Methods: EEG data were obtained during induction, maintenance, and emergence from 12 patients receiving customary anesthetic management for orthopedic, general, vascular, and neurosurgical procedures. These data were used to trigger the closely monitored execution of the various parts of the BIS Engine, allowing it to be reimplemented in a high-level language as an algorithm entitled ibis. Ibis was then rewritten for concision and physiological clarity to produce a novel completely clear-box depth-of-anesthesia algorithm titled openibis ., Results: The output of the ibis algorithm is functionally indistinguishable from the native BIS A-2000, with r = 0.9970 (0.9970-0.9971) and Bland-Altman mean difference between methods of -0.25 ± 2.6 on a unitless 0 to 100 depth-of-anesthesia scale. This precision exceeds the performance of any earlier attempt to reimplement the function of the BIS algorithms. The openibis algorithm also matches the output of the native algorithm very closely ( r = 0.9395 [0.9390-0.9400], Bland-Altman 2.62 ± 12.0) in only 64 lines of readable code whose function can be unambiguously related to observable features in the EEG signal. The operation of the openibis algorithm is described in an intuitive, graphical form., Conclusions: The openibis algorithm finally provides definitive answers about the BIS: the reliance of the most important signal components on the low-gamma waveband and how these components are weighted against each other. Reverse engineering allows these conclusions to be reached with a clarity and precision that cannot be obtained by other means. These results contradict previous review articles that were believed to be authoritative: the BIS score does not appear to depend on a bispectral index at all. These results put clinical anesthesia research using depth-of-anesthesia scores on a firm footing by elucidating their physiological basis and enabling comparison to other animal models for mechanistic research., Competing Interests: Conflicts of Interest: See Disclosures at the end of the article., (Copyright © 2022 International Anesthesia Research Society.)

In the aging brain, many of the alterations underlying cognitive and behavioral decline remain opaque. Caenorhabditis elegans offers a powerful model for aging research, with a simple, well-studied nervous system to further our understanding of the cellular modifications and functional alterations accompanying senescence. We perform multi-neuronal functional imaging across the aged C. elegans nervous system, measuring an age-associated breakdown in system-wide functional organization. At single-cell resolution, we detect shifts in activity dynamics toward higher frequencies. In addition, we measure a specific loss of inhibitory signaling that occurs early in the aging process and alters the systems' critical excitatory/inhibitory balance. These effects are recapitulated with mutation of the calcium channel subunit UNC-2/CaV2α. We find that manipulation of inhibitory GABA signaling can partially ameliorate or accelerate the effects of aging. The effects of aging are also partially mitigated by disruption of the insulin signaling pathway, known to increase longevity, or by a reduction of caspase activation. Data from mammals are consistent with our findings, suggesting a conserved shift in the balance of excitatory/inhibitory signaling with age that leads to breakdown in global neuronal dynamics and functional decline., Competing Interests: GW, JF, MA, CC, CG No competing interests declared, (© 2022, Wirak et al.)

The operation of the BIS monitor remains undescribed, despite 20 years of clinical use and 3000 academic articles. The core algorithmic software (the BIS Engine) can be retrieved from the motherboard of the A-2000 monitor in binary form through forensic disassembly using debugging interfaces left in place by the original designers, opening the possibility of executing the BIS algorithms on contemporary computers through emulation. Three steps were required for emulation. Firstly, the monitor input stage monitor was disassembled to determine how EEG signals can be compatibly presented to the Engine. Secondly, the Digital Signal Processor on which the Engine executes was recreated in software. Thirdly, the Engine code was patched, allowing execution separated from monitor hardware. Code performance under noise load was evaluated. EEG signals and BIS variables were obtained from a 13-year-old child in normal physiological sleep using a modern BIS monitor. BIS values in sleeping children exhibit a wide dynamic range, including values nominally associated with clinical anesthesia, providing a risk-free technique to obtain empirical EEG data that broadly exercise the algorithms. Emulation demonstrated a correlation coefficient of R = 0.943, consistent with correlations between official Engine iterations. Additive white noise in the EEG caused a progressive lifting and flattening of BIS values. Emulation replicates BIS Engine behavior, allowing calculation upon existing EEG datasets or signals from other, potentially remote or wireless, devices. Emulation provides advantages for elucidating the mathematical expression of the algorithms, which remain important as practical constraints on any hypothetical mechanism of action of anesthetics., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.)

Background: Modern consumer electronic devices and automobiles are often controlled by interfaces that sense physical gestures and spoken commands. In contrast, patient monitors and anesthesia devices are typically equipped with panel-mounted buttons, dials, and keyboards. The increased use of noncontact gesture-based interfaces in anesthesia may improve patient safety through more intuitive and prompter control of equipment and also through reduced rates of surface contamination. A novel gesture-based controller was designed and retrofitted to a standard GE Solar 8000M patient monitor. This type of technical innovation is rare, due to closely held proprietary input control systems on commercially produced clinical equipment. Nevertheless, we hypothesized that anesthesiologists would find a contactless gesture interface straightforward to use., Methods: A gesture-based interface system was developed to control a Solar 8000M patient monitor using a millimeter-wave radar sensor. The system was programmed to detect noncontact "rotate" and "press" gestures to control the patient monitor by implementing a virtual trim knob for interface control. Fifty anesthesiologists tested a prototype interface and evaluated usability by completing a short questionnaire incorporating modified Likert scales. These evaluations were performed in a nonpatient care environment so that respondents were not adversely task loaded during assessment, also allaying any ethical or safety concerns regarding use of this novel interface for patient management., Results: Anesthesia hardware was controlled reliably with 2 distinct gestures above the gesture sensor. The gesture-based interface generally was well received by anesthesiologists (8.09; confidence interval, 8.06-8.12 on a 10-point scale), who preferred the simpler "press" gesture to the "rotate" gesture (8.45; 8.39-8.51 vs 7.73; 7.67-7.79 on a 10-point scale; P = .005). The correlation between the preference scores for the 2 gestures from each anesthesiologist was strong (Pearson r = 0.49; 0.25-0.68; P < .001). Advancing level of training (resident, fellow, attending 1-10 years, attending >10 years) was not correlated with preference scores for either gesture (Spearman ρ = -0.02; -0.30 to 0.26; P = .87 for "press" and Spearman ρ = 0.08; -0.20 to 0.35; P = .58 for "rotate")., Conclusions: The use of gesture sensing for controlling anesthesia equipment was well received by a cohort of anesthesiologists. Even though the simpler "press" gesture was preferred over the "rotate" gesture, the intrarespondent correlation indicates that the preference for gestures as a whole is the stronger effect. No adverse relationship was found between acceptability and anesthesia experience level. Gesture sensing is a promising new area to simplify and improve the interaction between the anesthesiologist and the anesthesia workstation., Competing Interests: Conflicts of Interest: See Disclosures at the end of the article., (Copyright © 2020 International Anesthesia Research Society.)

Background: The bispectral index (BIS) monitor has been available for clinical use for >20 years and has had an immense impact on academic activity in Anesthesiology, with >3000 articles referencing the bispectral index. Despite attempts to infer its algorithms by external observation, its operation has nevertheless remained undescribed, in contrast to the algorithms of other less commercially successful monitors of electroencephalogram (EEG) activity under anesthesia. With the expiration of certain key patents, the time is therefore ripe to examine the operation of the monitor on its own terms through careful dismantling, followed by extraction and examination of its internal software., Methods: An A-2000 BIS Monitor (gunmetal blue case, amber monochrome display) was purchased on the secondary market. After identifying the major data processing and storage components, a set of free or inexpensive tools was used to retrieve and disassemble the monitor's onboard software. The software executes primarily on an ARMv7 microprocessor (Sharp/NXP LH77790B) and a digital signal processor (Texas Instruments TMS320C32). The device software can be retrieved directly from the monitor's hardware by using debugging interfaces that have remained in place from its original development., Results: Critical numerical parameters such as the spectral edge frequency (SEF), total power, and BIS values were retraced from external delivery at the device's serial port back to the point of their calculation in the extracted software. In doing so, the locations of the critical algorithms were determined. To demonstrate the validity of the technique, the algorithms for SEF and total power were disassembled, comprehensively annotated and compared to their theoretically ideal behaviors. A bug was identified in the device's implementation of the SEF algorithm, which can be provoked by a perfectly isoelectric EEG., Conclusions: This article demonstrates that the electronic design of the A-2000 BIS Monitor does not pose any insuperable obstacles to retrieving its device software in hexadecimal machine code form directly from the motherboard. This software can be reverse engineered through disassembly and decompilation to reveal the methods by which the BIS monitor implements its algorithms, which ultimately must form the definitive statement of its function. Without further revealing any algorithms that might be considered trade secrets, the manufacturer of the BIS monitor should be encouraged to release the device software in its original format to place BIS-related academic literature on a firm theoretical foundation and to promote further academic development of EEG monitoring algorithms.

Background: Animal studies demonstrate that anesthetic exposure during neurodevelopment can lead to persistent behavioral impairment. The changes in neuronal function underlying these effects are incompletely understood. Caenorhabditis elegans is well suited for functional imaging of postanesthetic effects on neuronal activity. This study aimed to examine such effects within the neurocircuitry underlying C. elegans locomotion., Methods: C. elegans were exposed to 8% isoflurane for 3 h during the neurodevelopmentally critical L1 larval stage. Locomotion was assessed during early and late adulthood. Spontaneous activity was measured within the locomotion command interneuron circuitry using confocal and light-sheet microscopy of the calcium-sensitive fluorophore GCaMP6s., Results: C. elegans exposed to isoflurane demonstrated attenuation in spontaneous reversal behavior, persisting throughout the animal's lifespan (reversals/min: untreated early adulthood, 1.14 ± 0.42, vs. isoflurane-exposed early adulthood, 0.83 ± 0.55; untreated late adulthood, 1.75 ± 0.64, vs. isoflurane-exposed late adulthood, 1.14 ± 0.68; P = 0.001 and 0.006, respectively; n > 50 animal tracks/condition). Likewise, isoflurane exposure altered activity dynamics in the command interneuron AVA, which mediates crawling reversals. The rate at which AVA transitions between activity states was found to be increased. These anesthetic-induced effects were more pronounced with age (off-to-on activity state transition time (s): untreated early adulthood, 2.5 ± 1.2, vs. isoflurane-exposed early adulthood, 1.9 ± 1.3; untreated late adulthood, 4.6 ± 3.0, vs. isoflurane-exposed late adulthood, 3.0 ± 2.4; P = 0.028 and 0.008, respectively; n > 35 traces acquired from more than 15 animals/condition). Comparable effects were observed throughout the command interneuron circuitry, indicating that isoflurane exposure alters transition rates between behavioral crawling states of the system overall. These effects were modulated by loss-of-function mutations within the FoxO transcription factor daf-16 and by rapamycin-mediated mechanistic Target of Rapamycin (mTOR) inhibition., Conclusions: Altered locomotive behavior and activity dynamics indicate a persistent effect on interneuron dynamics and circuit function in C. elegansafter developmental exposure to isoflurane. These effects are modulated by a loss of daf-16 or mTOR activity, consistent with a pathologic activation of stress-response pathways.

Background: A comprehensive understanding of how anesthetics facilitate a reversible collapse of system-wide neuronal function requires measurement of neuronal activity with single-cell resolution. Multineuron recording was performed in Caenorhabditis elegans to measure neuronal activity at varying depths of anesthesia. The authors hypothesized that anesthesia is characterized by dyssynchrony between neurons resulting in a collapse of organized system states., Methods: Using light-sheet microscopy and transgenic expression of the calcium-sensitive fluorophore GCaMP6s, a majority of neurons (n = 120) in the C. elegans head were simultaneously imaged in vivo and neuronal activity was measured. Neural activity and system-wide dynamics were compared in 10 animals, progressively dosed at 0%, 4%, and 8% isoflurane. System-wide neuronal activity was analyzed using principal component analysis., Results: Unanesthetized animals display distinct global neuronal states that are reflected in a high degree of correlation (R = 0.196 ± 0.070) between neurons and low-frequency, large-amplitude neuronal dynamics. At 4% isoflurane, the average correlation between neurons is significantly diminished (R = 0.026 ± 0.010; P < 0.0001 vs. unanesthetized) and neuron dynamics shift toward higher frequencies but with smaller dynamic range. At 8% isoflurane, interneuronal correlations indicate that neuronal activity remains uncoordinated (R = 0.053 ± 0.029; P < 0.0001 vs. unanesthetized) with high-frequency dynamics that are even further restricted. Principal component analysis of unanesthetized neuronal activity reveals distinct structure corresponding to known behavioral states. At 4% and 8% isoflurane this structure is lost and replaced with randomized dynamics, as quantified by the percentage of total ensemble variance captured by the first three principal components. In unanesthetized worms, this captured variance is high (88.9 ± 5.4%), reflecting a highly organized system, falling significantly at 4% and 8% isoflurane (57.9 ± 11.2%, P < 0.0001 vs. unanesthetized, and 76.0 ± 7.9%, P < 0.001 vs. unanesthetized, respectively) and corresponding to increased randomization and collapse of system-wide organization., Conclusions: Anesthesia with isoflurane in C. elegans corresponds to high-frequency randomization of individual neuron activity, loss of coordination between neurons, and a collapse of system-wide functional organization.

Commercial applications of artificial intelligence and machine learning have made remarkable progress recently, particularly in areas such as image recognition, natural speech processing, language translation, textual analysis, and self-learning. Progress had historically languished in these areas, such that these skills had come to seem ineffably bound to intelligence. However, these commercial advances have performed best at single-task applications in which imperfect outputs and occasional frank errors can be tolerated.The practice of anesthesiology is different. It embodies a requirement for high reliability, and a pressured cycle of interpretation, physical action, and response rather than any single cognitive act. This review covers the basics of what is meant by artificial intelligence and machine learning for the practicing anesthesiologist, describing how decision-making behaviors can emerge from simple equations. Relevant clinical questions are introduced to illustrate how machine learning might help solve them-perhaps bringing anesthesiology into an era of machine-assisted discovery.

Expected values for blood pressure are known for both unanesthetized and anesthetized children. The statistics of changes in blood pressure during anesthesia, which may have important diagnostic significance, have not been reported. The purpose of this study was to report the variation in changes in blood pressure in four pediatric age groups, undergoing both cardiac and non-cardiac surgery. An analysis of the changes in blood pressure using normalization and principal component analysis techniques was performed using an existing electronic dataset of intra-arterial pediatric blood pressure values during anesthesia. Cardiac and noncardiac cases were analyzed separately. For 1361 non-cardiac cases, the average systolic blood pressure increased from 55.2 (17.6) mmHg in the first month of life to 85.4 (17.7) mmHg at 5-6 years. For 912 cardiac cases, the average systolic blood pressure increased from 55.7 (16.7) to 71.8 (24.8) mmHg in these cohorts. For non-cardiac cases in the first month, the mean (SD) for change in blood pressure over a 30 s period was 0.00 (8.8), for 5-6 year olds 0.0 (7.4); for cardiac cases, 0.1 (9.2) to - 0.1 (9.2). Variations in systolic blood pressure over a 5-min period were wider: in non-cardiac from 0.1 (12.2) mmHg (first month) to 0.4 (11.5) mmHg (5-6 year old) and from 0.2 (12.5) to 0.4 (14.2) mmHg in cardiac cases. Absolute blood pressures and changes in blood pressure during anesthesia in pediatric cardiac and non-cardiac surgical cases have been analyzed from a population database. Using these values, the quantitative methods of normalization and principal component analysis allow the identification of statistically significant changes.

The ability to monitor the inspired and expired concentrations of volatile anesthetic gases in real time makes these drugs implicitly targetable. However, the end-tidal concentration only represents the concentration within the brain and the vessel rich group (VRG) at steady state, and very poorly approximates the VRG concentration during common dynamic situations such as initial uptake and emergence. How should the vaporization of anesthetic gases be controlled in order to optimally target VRG concentration in clinical practice? Using a generally accepted pharmacokinetic model of uptake and redistribution, a transfer function from the vaporizer setting to the VRG is established and transformed to the time domain. Targeted actuation of the vaporizer in a time-optimal manner is produced by a variable structure, sliding mode controller. Direct mathematical application of the controller produces rapid cycling at the limits of the vaporizer, further prolonged by low fresh gas flows. This phenomenon, known as "chattering", is unsuitable for operating real equipment. Using a simple and clinically intuitive modification to the targeting algorithm, a variable low-pass boundary layer is applied to the actuation, smoothing discontinuities in the control law and practically eliminating chatter without prolonging the time taken to reach the VRG target concentration by any clinically significant degree. A model is derived for optimum VRG-targeted control of anesthetic vaporizers. An alternate and further application is described, in which deliberate perturbation of the vaporization permits non-invasive estimation of parameters such as cardiac output that are otherwise difficult to measure intra-operatively.

What We Already Know About This Topic: WHAT THIS ARTICLE TELLS US THAT IS NEW: BACKGROUND:: Previous work on the action of volatile anesthetics has focused at either the molecular level or bulk neuronal measurement such as electroencephalography or functional magnetic resonance imaging. There is a distinct gulf in resolution at the level of cellular signaling within neuronal systems. The authors hypothesize that anesthesia is caused by induced dyssynchrony in cellular signaling rather than suppression of individual neuron activity., Methods: Employing confocal microscopy and Caenorhabditis elegans expressing the calcium-sensitive fluorophore GCaMP6s in specific command neurons, the authors measure neuronal activity noninvasively and in parallel within the behavioral circuit controlling forward and reverse crawling. The authors compare neuronal dynamics and coordination in a total of 31 animals under atmospheres of 0, 4, and 8% isoflurane., Results: When not anesthetized, the interneurons controlling forward or reverse crawling occupy two possible states, with the activity of the "reversal" neurons AVA, AVD, AVE, and RIM strongly intercorrelated, and the "forward" neuron AVB anticorrelated. With exposure to 4% isoflurane and onset of physical quiescence, neuron activity wanders rapidly and erratically through indeterminate states. Neuron dynamics shift toward higher frequencies, and neuron pair correlations within the system are reduced. At 8% isoflurane, physical quiescence continues as neuronal signals show diminished amplitude with little correlation between neurons. Neuronal activity was further studied using statistical tools from information theory to quantify the type of disruption caused by isoflurane. Neuronal signals become noisier and more disordered, as measured by an increase in the randomness of their activity (Shannon entropy). The coordination of the system, measured by whether information exhibited in one neuron is also exhibited in other neurons (multiinformation), decreases significantly at 4% isoflurane (P = 0.00015) and 8% isoflurane (P = 0.0028)., Conclusions: The onset of anesthesia corresponds with high-frequency randomization of individual neuron activity coupled with induced dyssynchrony and loss of coordination between neurons that disrupts functional signaling.

We describe a novel location and timekeeping system for a large, multifacility practice group using an app installed on mobile devices belonging to the staff. The system can be used independently of physical time clocks and without extracting information from anesthesia information management systems. The app creates geofences, reporting automatically when the user enters or departs the vicinity of a facility. The app displays the location of staff at all facilities, providing situational awareness. The leaving order of staff was adjusted daily using app data for the previous workload. This was successful; overtime was more evenly distributed year on year. Acceptance of the system was excellent.

An anesthesiologist must remain vigilant of the patient's clinical status, incorporating many independent physiological measurements. Oxygen saturation and heart rate are represented by continuous audible tones generated by the pulse oximeter, a mandated monitoring device. Other important clinical parameters--notably blood pressure--lack any audible representation beyond arbitrarily-configured threshold alarms. Attempts to introduce further continuous audible tones have apparently foundered; the complexity and interaction of these tones have exceeded the ability of clinicians to interpret them. Instead, we manipulate the tonal and rhythmic structure of the accepted pulse oximeter tone pattern melodically. Three melodic algorithms were developed to apply tonal and rhythmic variations to the continuous pulse oximeter tone, dependent on the systolic blood pressure. The algorithms distort the original audible pattern minimally, to facilitate comprehension of both the underlying pattern and the applied variations. A panel of anesthesia practitioners (attending anesthesiologists, residents and nurse anesthetists) assessed these algorithms in characterizing perturbations in cardiopulmonary status. Twelve scenarios, incorporating combinations of oxygen desaturation, bradycardia, tachycardia, hypotension and hypertension, were tested. A rhythmic variation in which additional auditory information was conveyed only at halftime intervals, with every other "beat" of the pulse oximeter, was strongly favored. The respondents also strongly favored the use of musical chords over single tones. Given three algorithms of tones embedded in the pulse oximeter signal, anesthesiologists preferred a melodic tone to signal a significant change in blood pressure.

Background: Previously we demonstrated that a computer algorithm based on bedside airway examinations and facial photographs accurately classified easy and difficult airways. The extent of the ability of anesthesiologists to perform the same task is unknown. We hypothesized that providing photographs would add to the predictive ability of anesthesiologists over that achieved when provided only with the Mallampati (MP) score and the thyromental distance (TMD). We further hypothesized that human observers would implicitly bias their predictions toward more sensitive determination of difficult airways, rather than more specific determination of easy airways., Methods: Residents, fellows, and attending anesthesiologists with varying levels of experience (N = 160) were presented with MP and TMD information from 80 Caucasian men subjects. The same subjects' data, accompanied by 3 facial photographs in head-on and right and left profiles, were also presented. Anesthesiologists classified the airways as easy or difficult according to specified criteria ("easy" defined as a single attempt with a Macintosh 3 blade resulting in a grade 1 laryngoscopic view; "difficult" defined as >1 attempt by an operator with at least 12 months anesthesia experience, grade 3 or 4 laryngoscopic view, need for a second operator, or nonelective use of an alternative airway device). Accuracy, sensitivity, and specificity were calculated for each anesthesiologist. We further developed a cost function to quantify a relative bias toward avoiding an unexpectedly difficult intubation versus overpreparing for an easy intubation., Results: One hundred sixty respondents completed the study. Presenting photographs improved respondents' sensitivity and accuracy in classifying airways, though specificity decreased slightly. Overall accuracy when given photographs was 61.6% (95% confidence interval, 60.8%-62.4%), which was significantly lower than the computer's performance of 87.5% (t test, P < 0.0001). Presentation of photographs, compared with MP and TMD alone, caused anesthesiologists to change their prediction from easy to difficult more frequently if the patients were obese (weight or body mass index), despite not having data on weight or height available. The cost function demonstrated that anesthesiologists strongly preferred to enhance sensitivity (detecting difficult airways) as compared with specificity (detecting easy airways), with a ratio of 6.5:1 (95% confidence interval, 4.9:1-8.4:1)., Conclusions: Anesthesiologists can derive useful information from facial appearance that enhances the prediction of a difficult airway over that achieved when presented with MP and TMD data alone. Anesthesiologists implicitly bias their predictions toward detection of difficult airways, compared with the true incidence of difficult airways, at the expense of accuracy and specificity. This behavior may be rational for cognitive tasks in which the costs of failure are strongly asymmetric.

We examined the proper performance of the Sellick maneuver, a maneuver used to reduce the risk of aspiration of stomach contents during induction of general anesthesia, using a novel device that measures and visualizes the force applied to the cricoid cartilage using thin-film force sensitive resistors in a form suitable for in vivo use. Performance was tested in three stages with twenty anaesthesiology residents and twenty trained operating room nurses. Firstly, subjects applied force to the cricoid cartilage as was customary to them. Secondly, subjects used the device to guide the application of that force. Thirdly, subjects were again asked to perform the manoeuvre without visual guidance. Each test lasted 1 min and the amount of force applied was measured throughout. Overall, the Sellick maneuver was often not applied properly, with large variance between individual subjects. Performance and inter-subject consistency improved to a very highly significant degree when subjects were able to use the device as a visual guide (p < 0.001). Subsequent significant improvements in performances during the last, unguided test demonstrated that the device initiated learning.

Introduction: Nitrogen (N2) narcosis could interfere with deep submarine escapes, particularly in the escape trunk, where simple but essential tasks are required in order to leave the submarine and start rapid ascent. In a previous study, we had suggested that prolongation of lungs-to-brain circulation time (LBct) may have a protective effect on N2 narcosis, a hypothesis tested in the present study., Materials and Methods: Computer software was designed to assess the effects of changes in circulation times on N2 uptake and distribution during the extremely rapid pressure changes typical of submarine escapes. Simulations of escapes from 600 to 1,000 fsw (with 200-fsw steps) were performed, with varying dwell times (DT) in the escape trunk (from 10 to 60 seconds, in 10-second steps). Baseline cardiac output (CO) was set at 5 liters/minute, and it was varied through changes in heart rate from 50% to 200% in the escape simulations. LBct was assumed to vary inversely with CO., Results: The risk of N2 narcosis was expressed as equivalent narcosis depth (END) in fsw, corresponding to N2 pressure in the brain after five minutes of air diving at that equivalent depth. The effects of changing CO on the highest END values (corresponding to the peak N2 pressures) reached while in the escape trunk or during entire escapes were tabulated. Depths at which peak N2 occurred were also analyzed. Prolonging LBct appeared to have two advantageous effects: 1. It reduced peak N2 reached both in the escape trunk and during the entire course of the escape 2. It delayed peak N2 to later stages of escapes (i.e., closer to the surface during ascent). These effects were more evident at greater escape depths and with longer DTs., Conclusions: Prolongation of LBct could protect against N2 narcosis and it could plausibly be achieved with the oral administration of a beta-blocker, such as propranolol, prior to deep submarine escape. Animal experiments should be conducted to validate this pharmacological approach.

Background: Bedside airway evaluation is conduced before anesthesia, but all current methods perform modestly, with low sensitivity and positive predictive value. We hypothesized that subjective features of patients' anatomies improve anesthesiologists' ability to predict difficult intubation, and derived a computer model to do so, based on analysis of photographs of patients' faces., Methods: Eighty male patients were divided into 2 equal cohorts for model derivation and validation. Each cohort consisted of 20 easy and 20 challenging intubations, defined as >1 attempt by an operator with at least 12 months of anesthesia experience, grade 3 or 4 laryngoscopic view, need for a second operator, or nonelective use of an alternative airway device. Photographs of each subject's face were analyzed by software that resolves each face into 61 facial proportions derived from an algorithm that models the face as a single point in a 50-dimensional eigenspace. Each parameter was tested for discriminatory ability by logistic regression, and combinations of 11 variables with P ≤ 0.1, plus Mallampati class and thyromental distance, were tested exhaustively by all possible binomial quadratic logistic regression models. Candidate models were cross-validated by maximizing the product of the area under the receiver operating characteristic curves obtained in the derivation and validation cohorts., Results: The best model included 3 facial parameters and thyromental distance. It correctly classified 70 of 80 subjects (P < 10(-8)). In contrast, the best combination of Mallampati class and thyromental distance correctly classified 47 of 80 (P = 0.073). Sensitivity, specificity, and area under the curve for the computer model were 90%, 85%, and 0.899, respectively., Conclusions: Computerized analysis of facial structure and thyromental distance can classify easy versus difficult intubation with accuracy significantly outperforming popular clinical predictive tests.

The U.S. Navy recommends submarine escape for depths down to 600 fsw, with deeper escapes entailing the risks of decompression sickness, nitrogen (N2) narcosis and CNS oxygen (O2) toxicity. However, the escape equipment, including the submarine escape and immersion equipment and the escape trunk, could probably function even at 1,000 fsw. Here we report a theoretical analysis of the risks of both N2 narcosis and CNS O2 toxicity for different escape profiles from 600 to 1,000 fsw. The effect of N2 narcosis, calculated as a function of N2 pressure in the brain using Gas Man software, was expressed as equivalent narcosis depth (END), corresponding to the depth at which the same pressure of N2 would be produced in the brain after five minutes of scuba diving with air. The risk of O2-induced convulsions was estimated using the model developed by Arieli et al. Different dwell times (DTs) at maximal pressure in the escape trunk (from 0 to 60 s) and lungs-to-brain circulation times (10 to 30 s) were included in our analysis. When DT in the escape trunk is very short (e.g., 10 s), the risk of either incapacitating N2 narcosis and/or O2-induced convulsions occurring in the trunk is low, even during escapes from 1,000 fsw.

Given a function that describes the uptake of a substance into the body with time, an analytical technique is described which transforms that function into a model of parallel first-order compartments that converges to the same uptake profile as the number of compartments is increased. The fitting of the compartmental model to the given uptake function is optimized to minimize the squared error. A necessary condition of the analytical method is that the uptake function be capable of being successively integrated at least as many times as the number of desired compartments. The uptake function should also be monotonically decreasing as all parallel first-order compartment models predict monotonically decreasing uptake. We applied this technique and ascertained the compartmental structure of the Severinghaus relationship, a longstanding observation in the field of clinical anesthesia that the uptake of nitrous oxide follows an inverse-square-root of time profile. The Severinghaus relationship is numerically poorly behaved at a time of zero elapsed minutes, predicting an instantaneously infinite uptake. Nevertheless, modeling of the first minute of anesthesia is necessary for characterizing the initial induction of anesthesia and methods of maintaining closed-circuit anesthesia such as the unit dose method. Using solely analytical methods, solutions for the compartmental properties of a mammillary model that matches the Severinghaus relationship for any expressed time interval are produced. These properties are compared to currently accepted values for the uptake of nitrous oxide. When matched to the Severinghaus relationship in the range of 0-100 min with a three-compartment model, we identified time constants of 0.28, 4.69 and 33.49 min with associated apparent volumes of 1.44, 2.14 and 7.97 l, respectively. The time constants in particular contrast to our earlier findings for the range of 1-100 min (1.46, 7.41 and 42.0 min). Our earlier findings were well matched to published time constants for tissues in classical pharmacokinetic models for volatile uptake. Consequently, we conclude that rigid adherence to the Severinghaus relationship from a time of zero minutes may lead to the over-administration of anesthetic agent due to an implicit mischaracterization of the relevant compartmental properties.

Threshold systolic arterial pressure alarms often use pre-operative values as a guide for intra-operative values. Recently, two systems (normalisation and principal component analysis) have been described that use the 'current' systolic arterial pressure and the change in systolic arterial pressure over a preceding time interval to generate an alarm based on units of standard deviation. Normalisation and principal component analysis techniques should prioritize alarms for clinically significant changes and hence reduce overall activation of alarms. Our aim was to measure the change in alarm activation using these techniques compared with standard threshold alarms. Systolic blood pressure data, collected from 10 patients (a total of 2177 min at 100 Hz), were cleaned and submitted to analysis using threshold alarms, normalisation and principal component analysis. With the threshold alarms set at 100 mmHg (low) and 140 mmHg (high), and a 5-min window, the alarms were activated for 557 min; using statistics-based thresholds the alarms were activated for 169 min (normalisation) and 155 min (principal component analysis), a reduction of approximately 70-72%.

For nitrous oxide, the first anesthetic for which uptake was measured in humans, Severinghaus noted empirically that a plot of the log of uptake against the log of elapsed time produced a straight line with slope -0.5, suggesting that uptake is proportional to the inverse square root of time. This result is something of a black box model, based on empirical curve fitting without regard to physiology. Some authors (e.g., Lowe) repeatedly returned to this inverse square root of time model as a benchmark while others (e.g., Hendrickx) questioned its validity and demanded the relationship be expressed with a physiologic model whose structure matches the known physiology being modeled. Nevertheless, the fact that authors have repeatedly come back to this inverse square root of time model as a benchmark suggests that it might have some underlying validity which has not previously been recognized. We re-explored this mathematically in an attempt to reveal hitherto undiscovered insights or limitations. In this study, we examined the square root of time model (viewed as a power function) and compared it with multi-compartment models. Further, we explored the stability of this relationship to systematic variation in the power value and also to the superimposition of noise-like perturbations, seeking conditions under which it might not work. Based upon this theoretical analysis, we also speculate on the existence of a physiological compartment with a time constant between that of the vessel-rich group (VRG) and muscle, and what the identity of such a compartment might be.

We have developed an anaesthesia alarm system that responds in a more clinically appropriate manner than current threshold alarms. A decrease in systolic arterial pressure of 10 mmHg from a previous value of 70 mmHg has a greater clinical significance than a decrease of 10 mmHg from 150 mmHg. However, it has been difficult to envisage a simple algorithm for the detection of these contextually adverse changes in physiological variables. We have processed systolic arterial pressure data to create a mathematically straightforward statistical tool for sampling intervals up to 5 min. Both the blood pressure and the change in blood pressure over a known time interval are plotted on x and y axes with the units in standard deviations. Some 10 824 measurements were obtained at 10-s intervals in 17 patients. The mean (SD) systolic arterial pressure for all observations in our patients was 118 (17.0) mmHg. The mean (SD) change in systolic arterial pressure over 5 min was - 0.35 (15.2) mmHg. Combining the value for the standard deviation of systolic arterial pressure and the standard deviation of the change in systolic arterial pressure using Pythagoras's theorem creates a value in standard deviations for this particular state. Instead of alarms being set in mmHg, they would be set in standard deviations. This technique was developed further using Principal Component Analysis to isolate uncommon deviations from normal, clinically unimportant physiological variations. These clinically unimportant changes occur in a predictable fashion only if the sampling interval is 90 s or less. This new alarm system is asymmetric - a small decrease in systolic arterial pressure from 90 mmHg may, appropriately, set off an alarm but it would require a much larger increase in systolic arterial pressure to do so.

The induction of temperature elevation by focused ultrasound is a noninvasive surgical technique for destroying tissue. This technique has been used clinically in soft tissues such as liver, prostate and breast. It has long been desired to extend this technique to noninvasive treatment of brain tumors. Although the skull was once thought to be an unsurpassable barrier to focused ultrasound treatment, it has been shown that the distortion caused by the skull can be corrected to produce a useful intracranial focus. However, the attenuation experienced by the ultrasound in passing through cranial bone is large, and consequently the skull is subject to the deposition of acoustic energy as heat. The nature and extent of this heating process has been difficult to characterize empirically. It is practically difficult to implant a sufficient number of thermocouples to obtain detailed temperature data directly, and bone is an unsuitable medium in which to perform noninvasive thermometry using proton chemical shift magnetic resonance imaging. Furthermore, skull specimens used experimentally lack active blood perfusion of the skull and the overlying scalp. This paper describes the use of large-scale acoustic and thermal simulations to calculate the distribution of temperature within the skull and brain that can be expected to occur during therapeutically useful focused ultrasound sonications of the brain. The results demonstrate that standing waves may be formed within the skull during transcranial sonication leading to nonuniform skull heating. However, the results also show that these effects can be sufficiently controlled to allow therapeutic ultrasound to be focused in the cranial base region of the brain without causing thermal damage to the scalp, skull or outer surface of the brain.

The density and structure of bone is highly heterogeneous, causing wide variations in the reported speed of sound for ultrasound propagation. Current research on the propagation of high intensity focused ultrasound through an intact human skull for non-invasive therapeutic action on brain tissue requires a detailed model for the acoustic velocity in cranial bone. Such models have been difficult to derive empirically due to the aforementioned heterogeneity of bone itself. We propose a single unified model for the speed of sound in cranial bone based upon the apparent density of bone by CT scan. This model is based upon the coupling of empirical measurement, theoretical acoustic simulation and genetic algorithm optimization. The phase distortion caused by the presence of skull in an acoustic path is empirically measured. The ability of a theoretical acoustic simulation coupled with a particular speed-of-sound model to predict this phase distortion is compared against the empirical data, thus providing the fitness function needed to perform genetic algorithm optimization. By performing genetic algorithm optimization over an initial population of candidate speed-of-sound models, an ultimate single unified model for the speed of sound in both the cortical and trabecular regions of cranial bone is produced. The final model produced by genetic algorithm optimization has a nonlinear dependency of speed of sound upon local bone density. This model is shown by statistical significance to be a suitable model of the speed of sound in bone. Furthermore, using a skull that was not part of the optimization process, this model is also tested against a published homogeneous speed-of-sound model and shown to return an improved prediction of transcranial ultrasound propagation.

It is well known that the acoustic properties of soft tissue have a dependence on tissue temperature. This is of particular interest in focused ultrasound surgery since the mechanism of action of focused ultrasound surgery is to kill targeted tissue by inducing localized heating by ultrasound absorption, and hence cautery of that tissue. However, the act of localized heating induces a change in the acoustic properties of the targeted tissue and tissue surrounding it. This phenomenon distorts the incoming acoustic wavefront, and has been termed the thermal lens effect for this reason. Furthermore, nonlinear effects in acoustic propagation become non-negligible at the ultrasound intensities required for therapeutic action. This paper examines the importance of the thermal lens effect and nonlinear tissue properties by simulating a variety of clinically applicable phased array transducer configurations that have not yet been appropriately analysed using a full three-dimensional nonlinear treatment of acoustic propagation. The significance of the thermal lens effect is characterized by comparing the simulation of coupled acoustic and thermal propagation with an uncoupled treatment; neglecting thermal lensing typically produces a movement of 1 to 2 mm in the predicted position of the focus towards the transducer. The results also show that the classical methods of acoustic propagation can produce grossly erroneous results under certain clinically relevant transducer configurations and that an acoustic field scan with a hydrophone may not accurately predict therapeutic effect.

Susceptibility to motion sickness has been linked to aerobic fitness in several studies, however, these studies have not elucidated the underlying physiological mechanism by which increased aerobic fitness is related to a decreased ability to tolerate motion sickness stimuli. This pilot study provides further evidence of a relationship between aerobic fitness and motion sickness susceptibility. It also suggests that aerobic capacity is more specifically linked to signs and symptoms of vasomotor origin including stomach discomfort, nausea and/or vomiting, headache, and diaphoresis. By independently correlating vasomotor susceptibility and neurogenic susceptibility to maximum oxygen uptake, we find that vasomotor symptoms in particular are significantly increased in aerobically fit individuals. Larger studies should be conducted to confirm this relationship.

Fluoride uptake and retention on maxillary and mandibular incisors were compared using a conventional APF gel, a thixotropic gel, and a new pluronic-based fluoride gel. Based on the results of in vivo acid-etch biopsies, significant fluoride uptake was obtained with each of the three agents. The highly viscous pluronic gel may provide an alternative to conventional topical fluoride gels for subjects--e.g., handicapped persons--with whom a tray system is not feasible.