Implementation of a Bayesian based advisory tool for target-controlled infusion of propofol using qCON as control variable.

This single blinded randomized controlled trial aims to assess whether the application of a Bayesian-adjusted CePROP (effect-site of propofol) advisory tool leads towards a more stringent control of the cerebral drug effect during anaesthesia, using qCON as control variable. 100 patients scheduled for elective surgery were included and randomized into a control or intervention group (1:1 ratio). In the intervention group the advisory screen was made available to the clinician, whereas it was blinded in the control group. The settings of the target-controlled infusion pumps could be adjusted at any time by the clinician. Cerebral drug effect was quantified using processed EEG (CONOX monitor, Fresenius Kabi, Bad Homburg, Germany). The time of qCON between the desired range (35-55) during anaesthesia maintenance was defined as our primary end point. Induction parameters and recovery times were considered secondary end points and coefficient of variance of qCON and CePROP was calculated in order to survey the extent of control towards the mean of the population. The desired range of qCON between 35 and 55 was maintained in 84% vs. 90% (p = 0.15) of the case time in the control versus intervention group, respectively. Secondary endpoints showed similar results in both groups. The coefficient of variation for CePROP was higher in the intervention group. The application of the Bayesian-based CePROP advisory system in this trial did not result in a different time of qCON between 35 and 55 (84 [21] vs. 90 [18] percent of the case time). Significant differences between groups were hard to establish, most likely due to a very high performance level in the control group. More extensive control efforts were found in the intervention group. We believe that this advisory tool could be a useful educational tool for novices to titrate propofol effect-site concentrations.

Trehalose-6-phosphate signaling regulates lateral root formation in Arabidopsis thaliana.

Plant roots explore the soil for water and nutrients, thereby determining plant fitness and agricultural yield, as well as determining ground substructure, water levels, and global carbon sequestration. The colonization of the soil requires investment of carbon and energy, but how sugar and energy signaling are integrated with root branching is unknown. Here, we show through combined genetic and chemical modulation of signaling pathways that the sugar small-molecule signal, trehalose-6-phosphate (T6P) regulates root branching through master kinases SNF1-related kinase-1 (SnRK1) and Target of Rapamycin (TOR) and with the involvement of the plant hormone auxin. Increase of T6P levels both via genetic targeting in lateral root (LR) founder cells and through light-activated release of the presignaling T6P-precursor reveals that T6P increases root branching through coordinated inhibition of SnRK1 and activation of TOR. Auxin, the master regulator of LR formation, impacts this T6P function by transcriptionally down-regulating the T6P-degrader trehalose phosphate phosphatase B in LR cells. Our results reveal a regulatory energy-balance network for LR formation that links the 'sugar signal' T6P to both SnRK1 and TOR downstream of auxin.

Influence of Remifentanil on the Control Performance of the Bispectral Index Controlled Bayesian-Based Closed-Loop System for Propofol Administration.

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.

The History of Target-Controlled Infusion.

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.

Accuracy of the composite variability index as a measure of the balance between nociception and antinociception during anesthesia.

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.

The accuracy and clinical feasibility of a new bayesian-based closed-loop control system for propofol administration using the bispectral index as a controlled variable.

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.

Robust predictive control strategy applied for propofol dosing using BIS as a controlled variable during anesthesia.

This paper presents the application of predictive control to drug dosing during anesthesia in patients undergoing surgery. The performance of a generic predictive control strategy in drug dosing control, with a previously reported anesthesia-specific control algorithm, has been evaluated. The robustness properties of the predictive controller are evaluated with respect to inter- and intrapatient variability. A single-input (propofol) single-output (bispectral index, BIS) model of the patient has been assumed for prediction as well as for simulation. A set of 12 patient models were studied and interpatient variability and disturbances are used to assess robustness of the controller. Furthermore, the controller guarantees the stability in a desired range. The applicability of the predictive controller in a real-life environment via simulation studies has been assessed.

The relationship between bispectral index and propofol during target-controlled infusion anesthesia: a comparative study between children and young adults.

BACKGROUND: In this prospective study, we compared the relationship between propofol concentrations and bispectral index (BIS) in children versus young adults anesthetized with target-controlled infusion (TCI) of propofol. METHODS: Forty-five prepubertal subjects (children) and 45 postpubertal subjects (adults) were studied. All patients were anesthetized with TCI of propofol, based on the Kataria et al.'s model for children and on the Schnider et al.'s model for adults. All data from the BIS and the TCI system were continuously recorded using Rugloop software. Remifentanil was continuously administered throughout the study (0.25 microg x kg(-1) x min(-1)). In all patients, after the end of surgery, a 12-min period with a stable target plasma concentration (Ct) of propofol, randomly assigned at 2, 3, 4, 5, and 6 microg/mL, was performed. In addition, in most of the patients, another 12-min period was performed during which the BIS was targeted at 50 +/- 5. After each 12-min steady-state period, the Ct and BIS were noted and the plasma concentration of propofol was measured (Cm). The Ct and Cm corresponding to half maximal effect (BIS(50)) was determined by the Hill equation, and by targeting BIS at 50. RESULTS: In children, as in adults, BIS values were highly correlated with the corresponding Ct or Cm of propofol following classical E(max) dose-response curves. The ECt(50) and the ECm(50), derived from the dose-response curves, were higher in children than in adults: ECm(50): 4.0 (3.6-4.5) microg/mL vs 3.3 (3.0-3.7) microg/mL [mean (95% CI)], P < 0.001; as well were the Ct and Cm clinically obtained when BIS was targeted at 50 (Cm(50): 4.3 +/- 1.1 microg/mL vs 3.4 +/- 1.2 microg/mL, (mean +/- SD) P < 0.05, children versus adults). Cm was generally under-estimated by the Ct, and the bias was higher in children than in adults: 2.6 +/- 2.6 microg/mL vs 1.7 +/- 1.6 microg/mL (P = 0.05). CONCLUSIONS: The good relationship between propofol and BIS demonstrated in children as in adults suggested a slightly lower sensitivity to propofol in children. As the predictability of plasma propofol concentrations with the classical pharmacokinetic/pharmacodynamic models is limited in children, a cerebral pharmacodynamic feedback, such as BIS, may be useful in this population.

Estimation of optimal modeling weights for a Bayesian-based closed-loop system for propofol administration using the bispectral index as a controlled variable: a simulation study.

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.

Closed loops in anaesthesia.

Closed-loop systems are able to make their own decisions and to try to reach and maintain a preset target. As a result, they might help the anaesthetist to optimise the titration of drug administration without any overshoot, controlling physiological functions and guiding monitoring variables. Thanks to the development of fast computer technology and more reliable pharmacological effect measures, the study of automation in anaesthesia has regained popularity. This short review focuses on the most recently developed and tested feedback systems in anaesthesia. Various new approaches for controlling the administration of intravenous and inhaled hypnotic-anaesthetic drugs have recently been published. For analgesics, a framework for further research has been presented in the literature. For other drugs, such as muscle relaxants and haemodynamic agents, only short reviews can be found. Until now, most of these systems have had to be under development. The challenge is now fully to establish the safety, efficacy, reliability and utility of closed-loop anaesthesia so that it can be adopted in the clinical setting. Besides, their role in optimising the controlled variables and control models, these systems have to be tested in extreme circumstances in order to test their robustness.

Performance evaluation of two published closed-loop control systems using bispectral index monitoring: a simulation study.

BACKGROUND: Although automated closed-loop control systems may improve quality of care, their safety must be proved under extreme control conditions. This study describes a simulation methodology to test automated controllers and its application in a comparison of two published controllers for Bispectral Index (BIS)-guided propofol administration. METHODS: A patient simulator was developed to compare controllers. Using input scripts to dictate patient characteristics, target BIS values, and the time course of surgical events, the simulator continuously monitors the infusion pump under control and generates BIS values as a composite of modeled response to drug, perceived stimulation, and random noise. The simulator formats the output stream of BIS data as input to the controller under test to emulate the serial output of the actual BIS monitor. A published model-based controller and a classic proportional integral derivative controller were compared when using the BIS value as a controlled variable. Each controller was tested using a set of 10 virtual patients undergoing a fixed surgical profile that was repeated with BIS targets set at 30, 50, and 70. Controller performance was assessed using median (absolute) prediction error, divergence, wobble, and percentage time within BIS target range metrics. RESULTS: The median prediction error was significantly smaller for the proportional integral derivative controller than for the model-based controller. The median absolute prediction error was smaller for the model-based controller than for the proportional integral derivative controller for each BIS target, reaching statistical significance for targets 30 and 50. CONCLUSIONS: When simulating closed-loop control of BIS using propofol, the use of a patient-individualized, model-based adaptive closed-loop system with effect site control resulted in better control of BIS compared with a standard proportional integral derivative controller with plasma site control. Even under extreme conditions, the modeled-based controller exhibited no behavioral problems.

Closed-loop control of anaesthesia.

PURPOSE OF REVIEW: Closed-loop systems are able to make decisions on their own and try to reach and maintain a preset target. As a result, they might help the anaesthesiologist in optimizing the titration of drug administration without overshooting, controlling physiological functions and guiding monitoring variables. Thanks to the development of fast computer technology and more reliable pharmacological effect measures, the study of automation in anaesthesia has regained popularity. RECENT FINDINGS: This short review focuses on the most recently developed and tested feed-back systems in anaesthesia. Various new approaches for controlling the administration of intravenous and inhaled hypnotic-anaesthetic drugs have been published recently. For analgesics, a framework for further research has been presented in the literature. For other drugs, such as muscle relaxants and haemodynamics, a short review can be found. SUMMARY: Until now, most of these systems are still under development. The challenge is now to establish fully the safety, efficacy, reliability and utility of closed-loop anaesthesia for its adoption into the clinical setting. Besides the optimization of controlled variables and control models, these systems have to be tested in extreme circumstances.