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Background: In the University Medical Center Groningen in Groningen, the Netherlands, moderate-to-deep sedation is provided by nursing staff trained and supervised by the anesthesia department using protocol-based target-controlled infusions (TCIs) of propofol and remifentanil. The aim of this retrospective cohort study was to investigate the incidence of events with potential adverse health consequences within this service model and the risk factors for the occurrence of these events., Methods: We retrospectively interrogated a database containing the computerized anesthetic records of 2937 procedures where moderate-to-deep sedation was provided using TCI administration of propofol and remifentanil between May 2014 and October 2017. The primary outcome measures were the incidence of sedation-related events with potential adverse health consequences and risk factors for the occurrence of such events. The events under investigation were unplanned intensive care unit (ICU) admission, need for cardiopulmonary resuscitation (CPR), death on the day of the procedure due to sedation-related events, cardiovascular events (arrhythmias, hypertension, and hypotension), pulmonary events (aspiration, desaturation, unplanned tracheal intubation), anaphylactic or allergic reactions, and the termination of the procedure due to sedation-related events. Cardiovascular and pulmonary events were classified as severe, significant, or moderate. Events were identified by using computer algorithms to search the computerized records from all included procedures., Results: Data from 2937 procedures were analyzed. No patients suffered catastrophic events (death, need for CPR, or unplanned ICU admission). Thirty-two severe sedation-related events occurred in 32 procedures. Severe desaturation (0.6%; 95% confidence interval [CI], 0.4-0.9) and severe hypertension (0.2%; 95% CI, 0.04-0.37) were the most common severe events. Significant hypotension (8.8%; 95% CI, 7.73-9.77) and significant desaturation (1.6%; 95% CI, 1.12-2.02) were found to be the most common events with potential adverse health consequences. No patient suffered lasting health consequences. Average mean and maximum targeted effect-site concentrations (Cet) for propofol were 2.6 ± 0.83 and 3.3 ± 1.09 µg·mL, respectively, and for remifentanil 0.84 ± 0.18 and 0.99 ± 0.22 ng·mL, respectively. Maximum Cets of propofol were lower among patients with higher body mass index (BMI) and were higher among patients of younger age. Higher BMI was a risk factor for desaturation. Increased age and lower BMI were risk factors for hypotension. Longer procedure time was a risk factor for both desaturation and hypotension., Conclusions: Moderate-to-deep sedation by propofol and remifentanil TCI has a low incidence of catastrophic and severe events.

Background: Clinicians can optimize propofol titration by using 2 sources of pharmacodynamic (PD) information: the predicted effect-site concentration for propofol (Ceprop) and the electroencephalographically (EEG) measured drug effect. Relation between these sources should be time independent, that is, perfectly synchronized. In reality, various issues corrupt time independency, leading to asynchrony or, in other words, hysteresis. This asynchrony can lead to conflicting information, making effective drug dosing challenging. In this study, we tried to quantify and minimize the hysteresis between the Ceprop (calculated using the Schnider model for propofol) and EEG measured drug effect, using nonlinear mixed-effects modeling (NONMEM). Further, we measured the influence of EEG-based monitor choice, namely Bispectral index (BIS) versus qCON index (qCON) monitor, on propofol PD hysteresis., Methods: We analyzed the PD data from 165 patients undergoing propofol-remifentanil anesthesia for outpatient surgery. Drugs were administered using target-controlled infusion (TCI) pumps. Pumps were programmed with Schnider model for propofol and Minto model for remifentanil. We constructed 2 PD models (direct models) relating the Schnider Ceprop to the measured BIS and qCON monitor values. We quantified the models' misspecification due to hysteresis, on an individual level, using the root mean squared errors (RMSEs). Subsequently, we optimized the PD models' predictions by adding a lag term to both models (lag-time PD models) and quantified the optimization using the RMSE., Results: There is a counterclockwise hysteresis between Ceprop and BIS/qCON values. Not accounting for this hysteresis results in a direct PD model with an effect-site concentration which produces 50% of the maximal drug effect (Ce50) of 6.24 and 8.62 µg/mL and RMSE (median and interquartile range [IQR]) of 9.38 (7.92-11.23) and 8.41(7.04-10.2) for BIS and qCON, respectively. Adding a modeled lag factor of 49 seconds to the BIS model and 53 seconds to the qCON model improved both models' prediction, resulting in similar Ce50 (3.66 and 3.62 µg/mL for BIS and qCON) and lower RMSE (median (IQR) of 7.87 (6.49-9.90) and 6.56 (5.28-8.57) for BIS and qCON., Conclusions: There is a significant "Ceprop versus EEG measured drug effect" hysteresis. Not accounting for it leads to conflicting PD information and false high Ce50 for propofol in both monitors. Adding a lag term improved the PD model performance, improved the "pump-monitor" synchrony, and made the estimates of Ce50 for propofol more realistic and less monitor dependent.

Background: This study investigated the clinical performance of a model-based, patient-individualized closed-loop (CL) control system for propofol administration using the bispectral index (BIS) as a controlled variable during the induction and maintenance of anesthesia with propofol and remifentanil and studied the influence of the targeted effect-site concentration of remifentanil (CeREMI) on its clinical performance., Methods: In 163 patients, propofol was administered using a CL system (BIS target [BISTARGET] between 40 and 50). Initial CeREMI targets between 2 and 7.5 ng/mL were selected as deemed clinically required. Performance parameters during induction were the time required to initially cross the target BIS, the time required to reach the maximal drug effect after induction (TPEAK, BIS) and the corresponding BIS at this moment, and the time required to regain the target BIS at the end of induction. Performance during maintenance was defined as the percentage of case time with target BIS ± 10 from target and the amount of performance error (PE) between the observed and target BIS values and its derived median PE (MDPE) as a measure of control bias, median absolute PE (MDAPE) as a measure of control inaccuracy, divergence as a measure of the time-related trend of the measured BIS values relative to the target BIS values, and wobble as a measure of intrasubject variability in prediction error. The secondary end point was the hemodynamic stability of the patient during CL control., Results: The applied CL system induced and maintained anesthesia within clinically accepted ranges. The percentage of case time [mean (standard deviation [SD]) across all study participants] with BIS ± 10 from the target was 82% (14%). The mean (SD) population MDPE and MDAPE were -6.6% (5.5%) and 11.2% (5.5%), respectively. A negative divergence [-0.001 (0.004)] and acceptable wobble [9.7% (4.0%)] were found. The correlation between the system PE and CeREMI was low and only influenced by a CeREMI <2.8 ng/mL. Hemodynamic stability stayed within the clinically acceptable range., Conclusions: The applied CL system for propofol administration has an acceptable performance in the CeREMI range of 2.8-7.5 ng/mL during the induction and maintenance of anesthesia. There was no evidence of a strong association between CeREM and the CL performance. This study also shows that when the CeREMI is <2.8 ng/mL, it might be more challenging to prevent arousal during propofol anesthesia.

Background: Brain monitors tracking quantitative brain activities from electroencephalogram (EEG) to predict hypnotic levels have been proposed as a labor-saving alternative to behavioral assessments. Expensive clinical trials are required to validate any newly developed processed EEG monitor for every drug and combinations of drugs due to drug-specific EEG patterns. There is a need for an alternative, efficient, and economical method., Methods: Using deep learning algorithms, we developed a novel data-repurposing framework to predict hypnotic levels from sleep brain rhythms. We used an online large sleep data set (5723 clinical EEGs) for training the deep learning algorithm and a clinical trial hypnotic data set (30 EEGs) for testing during dexmedetomidine infusion. Model performance was evaluated using accuracy and the area under the receiver operator characteristic curve (AUC)., Results: The deep learning model (a combination of a convolutional neural network and long short-term memory units) trained on sleep EEG predicted deep hypnotic level with an accuracy (95% confidence interval [CI]) = 81 (79.2-88.3)%, AUC (95% CI) = 0.89 (0.82-0.94) using dexmedetomidine as a prototype drug. We also demonstrate that EEG patterns during dexmedetomidine-induced deep hypnotic level are homologous to nonrapid eye movement stage 3 EEG sleep., Conclusions: We propose a novel method to develop hypnotic level monitors using large sleep EEG data, deep learning, and a data-repurposing approach, and for optimizing such a system for monitoring any given individual. We provide a novel data-repurposing framework to predict hypnosis levels using sleep EEG, eliminating the need for new clinical trials to develop hypnosis level monitors.

As most of us are aware, almost every facet of our society is becoming, for better or worse, progressively more technology-dependent. Technological advancement has made autonomous systems, also known as robots, an integral part of our life in several fields, including medicine. The application of robots in anesthesia could be classified into 3 types of robots. The first ones are pharmacological robots. These robots are based on closed-loop systems that allow better-individualized anesthetic drug titration for optimal homeostasis during general anesthesia and sedation. Recent evidence also demonstrates that autonomous systems could control hemodynamic parameters proficiently outperforming manual control in the operating room. The second type of robot is mechanical. They enable automated motorized reproduction of tasks requiring high manual dexterity level. Such robots have been advocated to be more accurate than humans and, thus, could be safer for the patient. The third type is a cognitive robot also known as decision support system. This type of robot is able to recognize crucial clinical situation that requires human intervention. When these events occur, the system notifies the attending clinician, describes relevant related clinical observations, proposes pertinent therapeutic options and, when allowed by the attending clinician, may even administer treatment. It seems that cognitive robots could increase patients' safety. Robots in anesthesia offer not only the possibility to free the attending clinicians from repetitive tasks but can also reduce mental workload allowing them to focus on tasks that require human intelligence such as analytical and clinical approach, lifesaving decision-making capacity, and interpersonal interaction. Nevertheless, further studies have yet to be done to test the combination of these 3 types of robots to maintain simultaneously the homeostasis of multiple biological variables and to test the safety of such combination on a large-scale population.

Background: Pulse oximetry-derived oxygen saturation is typically >97% in normoxia and hyperoxia, limiting its clinical use. The new Oxygen Reserve Index (ORi), a relative indicator of the partial pressure of oxygen dissolved in arterial blood (PaO2) in the range of 100-200 mm Hg, may allow additional monitoring of oxygen status., Methods: In this prospective validation intervention study, 20 healthy volunteers were breathing standardized oxygen concentrations ranging from mild hypoxia (fraction of inspired oxygen = 0.14) to hyperoxia (fraction of inspired oxygen = 1.0) via a tight-fitting face mask. ORi was measured noninvasively by multiwavelength pulse co-oximetry using 2 finger sensors. These ORi values (unitless scale, 0.00-1.00) were compared with measured PaO2 values. Repeated-measurements correlation analysis was performed to assess the ORi/PaO2 relationship. ORi trending ability was assessed using a 4-quadrant plot. The area under the receiver operating characteristics curve was calculated to assess the prediction of hypoxia (low-ranged PaO2, <100 mm Hg)., Results: Within the ORi-sensitive range, a strong positive correlation was found between ORi and PaO2 for both sensors (R = 0.78 and 0.83; P < .0001). ORi trending of PaO2 was good within this range (concordance rate = 94%). The prediction of PaO2 <100 mm Hg was also good, with an area under the receiver operating characteristics curve of 0.91 and 99% sensitivity and 82% specificity., Conclusions: In this prospective volunteer validation study, a strong and positive correlation between PaO2 and ORi was found, together with a good trending ability. Based on these data, the future use of ORi as a continuous noninvasive monitoring tool for assessing oxygenation status in patients receiving supplemental oxygen might be supported.

Maintaining brain function and integrity is a pivotal part of anesthesiological practice. The present overview aims to describe the current role of the 2 most frequently used monitoring methods for evaluation brain function in the perioperative period, ie, electroencephalography (EEG) and brain oxygenation monitoring. Available evidence suggests that EEG-derived parameters give additional information about depth of anesthesia for optimizing anesthetic titration. The effects on reduction of drug consumption or recovery time are heterogeneous, but most studies show a reduction of recovery times if anesthesia is titrated along processed EEG. It has been hypothesized that future EEG-derived indices will allow a better understanding of the neurophysiological principles of anesthetic-induced alteration of consciousness instead of the probabilistic approach most often used nowadays.Brain oxygenation can be either measured directly in brain parenchyma via a surgical burr hole, estimated from the venous outflow of the brain via a catheter in the jugular bulb, or assessed noninvasively by near-infrared spectroscopy. The latter method has increasingly been accepted clinically due to its ease of use and increasing evidence that near-infrared spectroscopy-derived cerebral oxygen saturation levels are associated with neurological and/or general perioperative complications and increased mortality. Furthermore, a goal-directed strategy aiming to avoid cerebral desaturations might help to reduce these complications. Recent evidence points out that this technology may additionally be used to assess autoregulation of cerebral blood flow and thereby help to titrate arterial blood pressure to the individual needs and for bedside diagnosis of disturbed autoregulation.

Background: Current electroencephalogram (EEG)-derived measures provide information on cortical activity and hypnosis but are less accurate regarding subcortical activity, which is expected to vary with the degree of antinociception. Recently, the neurophysiologically based EEG measures of cortical input (CI) and cortical state (CS) have been shown to be prospective indicators of analgesia/antinociception and hypnosis, respectively. In this study, we compared CI and an alternate measure of CS, the composite cortical state (CCS), with the Bispectral Index (BIS) and another recently developed measure of antinociception, the composite variability index (CVI). CVI is an EEG-derived measure based on a weighted combination of BIS and estimated electromyographic activity. By assessing the relationship between these indices for equivalent levels of hypnosis (as quantified using the BIS) and the nociceptive-antinociceptive balance (as determined by the predicted effect-site concentration of remifentanil), we sought to evaluate whether combining hypnotic and analgesic measures could better predict movement in response to a noxious stimulus than when used alone., Methods: Time series of BIS and CVI indices and the raw EEG from a previously published study were reanalyzed. In our current study, the data from 80 patients, each randomly allocated to a target hypnotic level (BIS 50 or BIS 70) and a target remifentanil level (Remi-0, -2, -4 or -6 ng/mL), were included in the analysis. CCS, CI, BIS, and CVI were calculated or quantified at baseline and at a number of intervals after the application of the Observer's Assessment of Alertness/Sedation scale and a subsequent tetanic stimulus. The dependency of the putative measures of antinociception CI and CVI on effect-site concentration of remifentanil was then quantified, together with their relationship to the hypnotic measures CCS and BIS. Finally, statistical clustering methods were used to evaluate the extent to which simple combinations of antinociceptive and hypnotic measures could better detect and predict response to stimulation., Results: Before stimulation, both CI and CVI differentiated patients who received remifentanil from those who were randomly allocated to the Remi-0 group (CI: Cohen's d = 0.65, 95% confidence interval, 0.48-0.83; CVI: Cohen's d = 0.72, 95% confidence interval, 0.56-0.88). Strong correlations between BIS and CCS were found (at different periods: 0.55 < R2 < 0.68, P < 0.001). Application of the Observer's Assessment of Alertness/Sedation stimulus was associated with changes in CI and CCS, whereas, subsequent to the application of both stimuli, changes in all measures were seen. Pairwise combinations of CI and CCS showed higher sensitivity in detecting response to stimulation than CVI and BIS combined (sensitivity [99% confidence interval], 75.8% [52.7%-98.8%] vs 42% [15.4%-68.5%], P = 0.006), with specificity for CI and CCS approaching significance (52% [34.7%-69.3%] vs 24% [9.1%-38.9%], P = 0.0159)., Conclusions: Combining electroencephalographically derived hypnotic and analgesic quantifiers may enable better prediction of patients who are likely to respond to tetanic stimulation.

Target-controlled infusions (TCIs) have been used in research and clinical practice for >2 decades. Nonapproved TCI software systems have been used during the conduct of almost 600 peer-reviewed published studies involving large numbers of patients. The first-generation pumps were first approved in 1996, and since then an estimated 25,000 units have been sold and used. Second-generation pumps were first approved in 2003. During 2004 to 2013, >36,000 units were sold. Currently, TCI systems are approved or available in at least 96 countries. TCI systems are used to administer propofol and opioids for IV sedation and general anesthesia for millions of patients every year. In countries where TCI systems are approved, nonapproved software is still commonly used in studies of the pharmacology of hypnotics and opioids, because research software offers greater flexibility than approved TCI systems. Research software is also readily integrated into data management modules. Although TCI is a part of established practice around the world, TCI devices have not received regulatory approval in the United States. In the United States, TCI administration of propofol and opioids for sedation and anesthesia is only possible using research software in IRB-approved research studies.

Target-controlled infusion (TCI) technology has been available in most countries worldwide for clinical use in anesthesia for approximately 2 decades. This infusion mode uses pharmacokinetic models to calculate infusion rates necessary to reach and maintain the desired drug concentration. TCI is computationally more complex than traditional modes of drug administration. The primary difference between TCI and conventional infusions is that TCI decreases the infusion rate at regular intervals to account for the uptake of drug into saturable compartments. Although the calculated infusion rates are consistent with manually controlled infusion rates, there are concerns that TCI administration of IV anesthetics could introduce unique safety concerns. After approximately 2 decades of clinical use, it is appropriate to assess the safety of TCI. Our aim in this article was to describe safety-relevant issues related to TCI, which should have emerged after its use in millions of patients. We collected information from published medical literature, TCI manufacturers, and publicly available governmental Web sites to find evidence of safety issues with the clinical use of TCI. Although many case reports emphasize that IV anesthesia is technically more demanding than inhaled anesthesia, including human errors associated with setting up IV infusions, no data suggest that a TCI mode of drug delivery introduces unique safety issues other than selecting the wrong pharmacokinetic model. This is analogous to the risk of selecting the wrong drug with current infusion pumps. We found no evidence that TCI is not at least as safe as anesthetic administration using constant rate infusions.

Target-controlled infusion (TCI) is a technique of infusing IV drugs to achieve a user-defined predicted ("target") drug concentration in a specific body compartment or tissue of interest. In this review, we describe the pharmacokinetic principles of TCI, the development of TCI systems, and technical and regulatory issues addressed in prototype development. We also describe the launch of the current clinically available systems.

Background: Remifentanil is a μ-opioid receptor agonist that was developed as a synthetic opioid for use in anesthesia and intensive care medicine. Remifentanil is rapidly metabolized in both blood and tissues, which results in a very short duration of action. Even after blood sampling, remifentanil is unstable in whole blood and plasma through endogenous esterases and chemical hydrolysis. The instability of remifentanil in these matrices makes sample collection and processing a critical phase in the bioanalysis of remifentanil., Methods: We have developed a fast and simple sample preparation method using protein precipitation followed by liquid chromatography-tandem mass spectrometry analysis. To improve the stability of remifentanil, citric acid, ascorbic acid, and formic acid were investigated for acidification of EDTA plasma. The stability of remifentanil was investigated in stock solution, EDTA whole blood, EDTA plasma, and acidified EDTA plasma at ambient temperature, 4 °C, 0 °C, and at -20 °C., Results: The analytical method was fully validated based on the Food and Drug Administration guidelines for bioanalytical method validation with a large linear range of 0.20 to 250 ng/mL remifentanil in EDTA plasma acidified with formic acid. The stability results of remifentanil in EDTA tubes, containing whole blood placed in ice water, showed a decrease of approximately 2% in 2 hours. EDTA plasma acidified with citric acid, formic acid, and ascorbic acid showed 0.5%, 4.2%, and 7.2% remifentanil degradation, respectively, after 19 hours at ambient temperature. Formic acid was chosen because of its volatility and thus liquid chromatography-tandem mass spectrometry compatibility. The use of formic acid added to EDTA plasma improved the stability of remifentanil, which was stable for 2 days at ambient temperature, 14 days at 4 °C, and 103 days at -20 °C., Conclusions: The analytical method we developed uses a simple protein precipitation and maximal throughput by a 2-point calibration curve and short run times of 2.6 minutes. Best sample stability is obtained by placing tubes containing EDTA whole blood in ice water directly after sampling, followed by centrifugation and transfer of the EDTA plasma to tubes with formic acid. The stability of remifentanil in EDTA plasma was significantly improved by the addition of 1.5 μL formic acid per milliliter of EDTA plasma. This analytical method and sample pretreatment are suitable for remifentanil pharmacokinetic studies.

Background: The Composite Variability Index (CVI), derived from the electroencephalogram, was developed to assess the antinociception-nociception balance, whereas the Bispectral Index (BIS) was developed to assess the hypnotic state during anesthesia. We studied the relationships between these indices, level of hypnosis (BIS level), and antinociception (predicted remifentanil effect-site concentrations, CeREMI) before and after stimulation. Also, we measured their association with movement in response to a noxious stimulus., Methods: We randomized 120 patients to one of 12 groups targeting different hypnotic levels (BIS 70, 50, and 30) and various CeREMI (0, 2, 4, or 6 ng/mL). At pseudo-steady state, baseline values were observed, and a series of stimuli were applied. Changes in BIS, CVI, heart rate (HR), and mean arterial blood pressure (MAP) between baseline and response period were analyzed in relation to level of hypnosis, antinociception, and somatic response to the stimuli., Results: CVI and BIS more accurately correlate with somatic response to an Observer Assessment of Alertness and Sedation-noxious stimulation than HR, MAP, CeREMI, and propofol effect-site concentration (Tukey post hoc tests P < 0.01). Change in CVI is more adequate to monitor response to stimulation than changes in BIS, HR, or MAP (as described by the Mathews Correlation Coefficient with significance level set at P < 0.001). In contrast, none of the candidate analgesic state indices was uniquely related to a specific opioid concentration and is extensively influenced by the hypnotic state as measured by BIS., Conclusions: CVI appears to correlate with somatic responses to noxious stimuli. However, unstimulated CVI depends more on hypnotic drug effect than on opioid concentration.

Background: Pharmacokinetic (PK) models are used to predict drug concentrations for infusion regimens for intraoperative displays and to calculate infusion rates in target-controlled infusion systems. For propofol, the PK models available in the literature were mostly developed from particular patient groups or anesthetic techniques, and there is uncertainty of the accuracy of the models under differing patient and clinical conditions. Our goal was to determine a PK model with robust predictive performance for a wide range of patient groups and clinical conditions., Methods: We aggregated and analyzed 21 previously published propofol datasets containing data from young children, children, adults, elderly, and obese individuals. A 3-compartmental allometric model was estimated with NONMEM software using weight, age, sex, and patient status as covariates. A predictive performance metric focused on intraoperative conditions was devised and used along with the Akaike information criteria to guide model development., Results: The dataset contains 10,927 drug concentration observations from 660 individuals (age range 0.25-88 years; weight range 5.2-160 kg). The final model uses weight, age, sex, and patient versus healthy volunteer as covariates. Parameter estimates for a 35-year, 70-kg male patient were: 9.77, 29.0, 134 L, 1.53, 1.42, and 0.608 L/min for V1, V2, V3, CL, Q2, and Q3, respectively. Predictive performance is better than or similar to that of specialized models, even for the subpopulations on which those models were derived., Conclusions: We have developed a single propofol PK model that performed well for a wide range of patient groups and clinical conditions. Further prospective evaluation of the model is needed.

Background: With the growing use of pharmacokinetic (PK)-driven drug delivery and/or drug advisory displays, identifying the PK model that best characterizes propofol plasma concentration (Cp) across a variety of dosing conditions would be useful. We tested the accuracy of 3 compartmental models and 1 physiologically based recirculatory PK model for propofol to predict the time course of propofol Cp using concentration-time data originated from studies that used different infusion schemes., Methods: Three compartmental PK models for propofol, called the "Marsh," the "Schnider," and the "Schüttler" models, and 1 physiologically based recirculatory model called the "Upton" model, were used to simulate the time course of propofol Cp. To test the accuracy of the models, we used published measured plasma concentration data that originated from studies of manual (bolus and short infusion) and computer-controlled (target-controlled infusion [TCI] and long infusion) propofol dosing schemes. Measured/predicted (M/P) propofol Cp plots were constructed for each dataset. Bias and inaccuracy of each model were assessed by median prediction error (MDPE) and median absolute prediction error (MDAPE), respectively., Results: The M/P propofol Cp in the 4 PK models revealed bias in all 3 compartmental models during the bolus and short infusion regimens. In the long infusion, a worse M/P propofol Cp at higher concentration was seen for the Marsh and the Schüttler models than for the 2 other models. Less biased M/P propofol Cp was found for all models during TCI. In the bolus group, after 1 min, a clear overprediction was seen for all 3 compartmental models for the entire 5 min; however, this initial error resolved after 4 min in the Schnider model. The Upton model did not predict propofol Cp accurately (major overprediction) during the first minute. During the bolus and short infusion, the Marsh model demonstrated worse MDPE and MDAPE compared with the 3 other models. During short infusion, MDAPE for the Schnider and Schüttler models was better than the Upton and the Marsh models. All models showed similar MDPE and MDAPE during TCI simulations. During long infusion, the Marsh and the Schüttler models underestimated the higher plasma concentrations., Conclusion: When combining the performance during various infusion regimens, it seems that the Schnider model, although still not perfect, is the recommended model to be used for TCI and advisory displays.

Background: Midazolam, at sedative levels, increases blood propofol concentrations by 25%. We evaluated the reverse interaction and determined the influence of propofol on the pharmacokinetics of midazolam., Methods: Eight healthy male volunteers were studied on 2 occasions in a random crossover manner. During session A, volunteers received midazolam 0.035 to 0.05 mg x kg(-1) IV for 1 minute followed by an infusion of 0.035 to 0.05 mg x kg(-1) x h(-1) for 59 minutes. During session B, in addition to this midazolam infusion scheme, a target-controlled infusion of propofol (constant C(T): 0.6 or 1.0 microg x mL(-1)) was given from 15 minutes before the start until 6 hours after termination of the midazolam infusion. Arterial blood samples for propofol and midazolam concentration analysis were taken until 6 hours after termination of the midazolam infusion. Nonlinear mixed-effect models examining the influence of propofol and hemodynamic variables on midazolam pharmacokinetics were constructed using Akaike's information-theoretic criterion for model selection., Results: In the presence of a mean blood propofol concentration of 1.2 microg x mL(-1), the plasma midazolam concentration was increased by 26.9% + or - 9.4% compared with midazolam given as a single drug. Propofol (C(blood): 1.2 microg x mL(-1)) reduced midazolam central volume of distribution from 5.37 to 2.98 L, elimination clearance from 0.39 to 0.31 L x min(-1), and rapid distribution clearance from 2.77 to 2.11 L x min(-1). Inclusion of heart rate further improved the pharmacokinetic model of midazolam., Conclusions: Propofol reduces the distribution and clearance of midazolam in a concentration-dependent manner. In addition, inclusion of heart rate as a covariate improved the pharmacokinetic model of midazolam predominantly through a reduction in the intraindividual variability.

Background: The combination of propofol-remifentanil for procedural deep sedation in spontaneously breathing patients is characterized by the frequent incidence of side effects, especially respiratory depression. These side effects may be due to either the drug combination or the drug delivery technique. Target-controlled infusion (TCI) might optimize drug delivery. In this prospective, randomized, double-blind study in patients undergoing elective colonoscopy, we thus tried to answer two questions: first, if adding remifentanil to propofol surpasses the disadvantages of the combination of these two products, and second, if administration of remifentanil via TCI decreases the incidence of side effects, compared to manually controlled administration., Methods: Patients undergoing elective colonoscopy were randomly assigned to receive remifentanil via manually controlled continuous infusion (MCI) (0.125 microg x kg(-1) x min(-1) for 2 min followed by a continuous infusion of 0.05 microg x kg(-1) x min(-1)), TCI remifentanil (1 ng/mL), or placebo (normal saline either as TCI or manual infusion of equivalent rate). All patients received TCI propofol, adjusted to a target concentration level that provided deep sedation in which patients were not responsive to verbal commands, but maintained spontaneous ventilation without assistance., Results: Significantly more patients in the placebo group showed movement, cough and hiccup, which transiently interfered with the examination. There were no clinically significant differences in hemodynamic or recovery variables among all groups. Remifentanil administered via TCI resulted in a decrease in propofol requirements. The incidence of hypopnea and apnea was less frequent when remifentanil was administered via TCI compared to MCI (TCI n = 7, MCI n = 16, P < 0.05)., Conclusion: The combination of remifentanil and propofol for deep sedation in spontaneously breathing patients, offered better conditions for colonoscopy than propofol used as a single drug. Remifentanil administered via TCI resulted in a decrease in propofol dosing and in a lower incidence in apnea and respiratory depression (TCI n = 7, MCI n = 16, P < 0.05), compared to manually controlled administration of remifentanil.

Background: To guide anesthetic administration with electroencephalogram monitors in children, an adequate characterization of the anesthetic effect measured by these monitors in this population is needed. We sought to quantify and compare the dynamic profile of sevoflurane's effect measured with the cerebral state index (CSI) and the bispectral index (BIS) in children., Methods: Fifteen healthy children, aged 3-15 yr, scheduled to undergo minor surgery were prospectively studied. During the simultaneous recording of CSI and BIS, the sevoflurane vaporizer was set at 6 vol % for 5 min and then decreased. End-tidal concentrations (C(ET)) were measured. The C(ET)-sevoflurane effect-site concentration equilibration and pharmacodynamics were modeled. Goodness of fit between models was compared. Data are typical value (coefficient of variation)., Results: Within the anesthetic depth range studied, the rate of change of sevoflurane's effect expressed as the effect-site equilibration half-life (t(1/2) k(e0)) was slower with the CSI [2.0 (14) min] than with BIS [1.2 (53) min] (P < 0.05). The estimated baseline effect of BIS and CSI before sevoflurane administration (E(0)) was 84 (39) for CSI and 87 (7) for BIS (NS). The sensitivity to sevoflurane hypnotic effect expressed in the C(50) [steady-state C(ET) eliciting half of the maximum response (E(max))] was 2.1 (68) % with CSI and 2.1 (16)% with BIS (NS). The E(max) with CSI 45 (0) was higher than that with BIS 27 (39) (P < 0.05). The population prediction error was significantly better for BIS (-0.7 +/- 26.9) than for CSI (-3.0 +/- 178.6) (P < 0.05)., Conclusions: In children, the t(1/2) k(e0) of sevoflurane and the pharmacodynamics of sevoflurane were quantified and the results were entirely dependent on the monitor used to measure its hypnotic effect. Within the anesthetic depth range studied, the rate of change of sevoflurane's effect was slower with the CSI. To adequately guide sevoflurane administration with these monitors in children, these differences should be considered.

Background: Closed-loop control of the hypnotic component of anesthesia has been proposed in an attempt to optimize drug delivery. Here, we introduce a newly developed Bayesian-based, patient-individualized, model-based, adaptive control method for bispectral index (BIS) guided propofol infusion into clinical practice and compare its accuracy and clinical feasibility under direct observation of an anesthesiologist versus BIS guided, effect compartment controlled propofol administration titrated by the anesthesiologist during ambulatory gynecological procedures., Methods: Forty ASA patients were randomly allocated to the closed-loop or manual control group. All patients received midazolam 1 mg IV and alfentanil 0.5 mg IV before induction. In the closed-loop control group, propofol was administered using the previously described closed-loop control system to reach and maintain a target BIS of 50. In the manual control group, the propofol effect-site concentration was adapted at the discretion of the anesthesiologist to reach and maintain a BIS as close as possible to 50. Induction characteristics, performance, and robustness during maintenance and recovery times were compared. Hemodynamic and respiratory stability were calculated as clinical feasibility parameters., Results: The closed-loop control system titrated propofol administration accurately resulting in BIS values close to the set point. The closed-loop control system was able to induce the patients within clinically accepted time limits and with less overshoot than the manual control group. Automated control resulted in beneficial recovery times. Our closed-loop control group showed similar acceptable clinical performance specified by similar hemodynamic, respiratory stability, comparable movement rates, and quality scores than the manual control group., Conclusions: The Bayesian-based closed-loop control system for propofol administration using the BIS as a controlled variable performed accurate during anesthesia for ambulatory gynecological procedures. This control system is clinical feasibility and can be further validated in clinical practice.

Background: Acute postoperative pain is common after most surgical procedures. Despite the availability of many analgesic options, postoperative pain management is often unsatisfactory. Purified capsaicin (ALGRX 4975 98% pure) has demonstrated prolong inhibition of C-fiber function in in vitro, preclinical, and clinical studies, and may be an effective adjunct to postoperative pain management., Methods: We performed a single-center, randomized, double-blind, placebo-controlled study of the analgesic efficacy of a single intraoperative wound instillation of 1000 microg ultrapurified capsaicin (ALGRX 4975) after open mesh groin hernia repair in 41 adult male patients. The primary end-point was average daily visual analog scale (VAS) pain scores during the first week after surgery assessed as area under the curve (AUC). Pain was recorded twice daily in a pain diary for 4 wk. Physical examination and laboratory tests were done before and 1 wk after surgery, together with recordings of adverse events up to 28 days. Adverse events were recorded. Data were also analyzed using a mixed-effects analysis with NONMEM., Results: VAS AUC was significantly lower during the first 3 days postoperatively (P < 0.05), but not for the whole 1 or 4 wk postoperatively. Mixed-effects analysis with NONMEM revealed that pain scores were significantly lower (P < 0.05) in the capsaicin group during the first 4 days. No clinically significant serious adverse events were observed, although a mild transient increase in liver enzymes was seen more often in the capsaicin-treated group., Conclusion: In the setting of a well-defined analgesic protocol standard, VAS AUC analysis and a mixed-effect analysis showed superior analgesia of capsaicin relative to placebo during the first 3-4 days after inguinal hernia repair.

Background: Intraarticular (IA) local anesthetics are often used for the management and prevention of pain after arthroscopic knee surgery. Recently, IA tramadol was also used for the management of these patients. However, the IA combination of local anesthetic and tramadol has not been evaluated in arthroscopic outpatients. Our primary aim in this study was to evaluate the analgesic effect of an IA combination of bupivacaine and tramadol when compared with each drug alone using visual analog scale (VAS) pain scores in patients undergoing day-care arthroscopic knee surgery. Additionally, we assessed analgesic demand., Methods: Ninety ASA I/II patients undergoing arthroscopic partial meniscectomy, performed by a single surgeon under general anesthesia, were assigned in a randomized, double-blind manner into three groups: group B (n = 30) received 0.25% bupivacaine, group T (n = 30) received 100 mg tramadol, and group BT (n = 30) received 0.25% bupivacaine and 100 mg tramadol to a total volume of 20 mL by the IA route after surgery. Postoperative pain scores were measured on a VAS, at rest and on mobilization at 0.5, 1, 2, 4, 6, 8, 12, and 24 h. Duration of analgesia, the subsequent 24 h consumption of rescue analgesia, time to ambulation, and time to discharge were evaluated. In addition, the systemic side effects of the IA injected drugs were also assessed., Results: The results showed significantly lower VAS pain scores in group BT (P << 0.1) when compared with groups T and B. Group BT had a later onset of postsurgical pain and longer time to first rescue analgesic than groups B and T. The 24 h consumption of analgesic was significantly less in group BT when compared with the other two groups (26.7% of the patients required rescue analgesia in group BT, whereas this number was 90% in group B and 86.7% in group T). In addition, time in hours to discharge and time to unassisted ambulation were significantly shorter in group BT when compared with groups T and B, and this was not associated with any detectable systemic effects., Conclusion: The IA admixture of tramadol 100 mg with bupivacaine 0.25% provides a pronounced prolongation of analgesia compared with either drug alone in patients undergoing day care arthroscopic knee surgery.

Background: Implementing Bayesian methods in a model-based closed-loop system requires the integration of a standard response model with a patient-specific response model. This process makes use of specific modeling weights, called Bayesian variances, which determine how the specific model can deviate from the standard model. In this study we applied simulations to select the Bayesian variances yielding the optimal controller for a Bayesian-based closed-loop system for propofol administration using the Bispectral Index (BIS) as a controlled variable., Methods: The relevant Bayesian variances determining the modeling process were identified. Each set of such Bayesian variances represents a potential controller. The set, which will result in optimal control, was estimated using calculations on a simulated population. We selected 625 candidate sets. Similar to our previous closed-loop performance study, we applied a simulation protocol to evaluate controller performance. Our population consisted of 416 virtual patients, generated using population characteristics from previous work. A BIS offset trajectory similar to a surgical case was used., Results: We were able to develop, describe, and optimize the parameter setting for a patient-individualized model-based closed-loop controller using Bayesian optimization. Selection of the optimal set yields a controller performing with the following median absolute prediction errors at BIS targets 30, 50, and 70: 12.9 +/- 2.87, 7.59 +/- 0.74, and 5.76 +/- 1.03 respectively., Conclusions: We believe this system can be introduced safely into clinical testing for both induction and maintenance of anesthesia under direct observation of an anesthesiologist.

In this study we investigated whether the novel reversal drug, sugammadex, is equally effective at reversing rocuronium-induced neuromuscular block (NMB) in patients under propofol or sevoflurane maintenance anesthesia. After receiving propofol for induction, patients were randomized to propofol (n = 21) or sevoflurane (n = 21). Rocuronium 0.6 mg/kg was administered for tracheal intubation. NMB was monitored using acceleromyography. At reappearance of the second twitch of the train-of-four ratio, sugammadex 2.0 mg/kg was administered by IV bolus. The primary end-point was time from start of sugammadex administration to recovery of train-of-four ratio to 0.9. Mean recovery time was 1.8 min after both propofol and sevoflurane anesthesia. The 95% confidence interval for the difference in recovery time between the 2 groups (-0.5 to +0.4 min) was well within the predefined equivalence interval (-1 to +1 min), indicating that recovery from NMB was unaffected by maintenance anesthesia. Thirteen patients (propofol n = 4; sevoflurane n = 9) experienced adverse events; these were treatment-related in 4 patients (propofol n = 3; sevoflurane n = 1). There were no treatment-related serious adverse events and no discontinuations or deaths. No residual paralysis occurred. The safety profile of sugammadex was somewhat more favorable under propofol than under sevoflurane anesthesia.

Unlabelled: There is concern about the toxicity of Compound (Co) A. Absorbents differ in the production of Co A during minimal-flow sevoflurane anesthesia. Strong alkali-free Amsorb does not produce Co A. It was our aim to study Superia, another new NaOH- and KOH-free CO(2) absorbent, in minimal-flow anesthesia, compared with KOH-free Sofnolime. After Ethics Committee approval, 14 consenting adult patients were included randomly by using Superia or Sofnolime as the CO(2) absorbent in the compact 750-mL canister of an ADU ventilator. After propofol and remifentanil administration, sevoflurane was given in oxygen and air (500 mL/min; fraction of inspired oxygen, 0.4), aiming at an end-tidal concentration of 2.3%-2.5%; ventilation aimed for 33-35 mm Hg PETCO(2). Compound A inspired (Co A(insp)) and expired (Co A(exp)) samples were taken for analysis, and canister temperatures were measured for 150 min. Statistical analysis was performed with the Friedman test or the Mann-Whitney U-test where appropriate. Correction for multiple testing was used. In the Superia group, no significant amount of Co A was formed, whereas in the Sofnolime group, maximum median (range) inspiratory values of 25 ppm (16 ppm) were found. The intergroup difference was P < 0.05. No difference was noticed between the two groups for the canister CO(2) absorbent temperature., Implications: During minimal-flow 2.3%-2.5% end-tidal sevoflurane, no compound A (Co A) is formed with the NaOH- and KOH-free CO(2) absorbent Superia. Although Co A values with KOH-free Sofnolime are still within reported safe limits, Superia is definitely an alternative for safe clinical practice.