A comparison of propofol-to-BIS post-operative intensive care sedation by means of target controlled infusion, Bayesian-based and predictive control methods: an observational, open-label pilot study.

PURPOSE: We evaluated the feasibility and robustness of three methods for propofol-to-bispectral index (BIS) post-operative intensive care sedation, a manually-adapted target controlled infusion protocol (HUMAN), a computer-controlled predictive control strategy (EPSAC) and a computer-controlled Bayesian rule-based optimized control strategy (BAYES). METHODS: Thirty-six patients undergoing short lasting sedation following cardiac surgery were included to receive propofol to maintain a BIS between 40 and 60. Robustness of control for all groups was analysed using prediction error and spectrographic analysis. RESULTS: Although similar time courses of measured BIS were obtained in all groups, a higher median propofol effect-site concentration (CePROP) was required in the HUMAN group compared to the BAYES and EPSAC groups. The time course analysis of the remifentanil effect-site concentration (CeREMI) revealed a significant increase in CeREMI in the EPSAC group compared to BAYES and HUMAN during the case. Although similar bias and divergence in control was found in all groups, larger control inaccuracy was observed in HUMAN versus EPSAC and BAYES. Spectrographic analysis of the system behavior shows that BAYES covers the largest spectrum of frequencies, followed by EPSAC and HUMAN. CONCLUSIONS: Both computer-based control systems are feasible to be used during ICU sedation with overall tighter control than HUMAN and even with lower required CePROP. EPSAC control required higher CeREMI than BAYES or HUMAN to maintain stable control. Clinical trial number: NCT00735631.

Influence of Bayesian optimization on the performance of propofol target-controlled infusion.

BACKGROUND: Target controlled infusion (TCI) systems use population-based pharmacokinetic (PK) models that do not take into account inter-individual residual variation. This study compares the bias and inaccuracy of a population-based vs a personalized TCI propofol titration using Bayesian adaptation. Haemodynamic and hypnotic stability, and the prediction probability of alternative PK models, was studied. METHODS: A double-blinded, prospective randomized controlled trial of 120 subjects undergoing cardiac surgery was conducted. Blood samples were obtained at 10, 35, 50, 65, 75 and 120 min and analysed using a point-of-care propofol blood analyser. Bayesian adaptation of the PK model was applied at 60 min in the intervention group. Median (Absolute) Performance Error (Md(A)PE) was used to evaluate the difference between bias and inaccuracy of the models. Haemodynamic (mean arterial pressure [MAP], heart rate) and hypnotic (bispectral index [BIS]) stability was studied. The predictive performance of four alternative propofol PK models was studied. RESULTS: MdPE and MdAPE did not differ between groups during the pre-adjustment period (control group: 6.3% and 16%; intervention group: 5.4% and 18%). MdPE differed in the post-adjustment period (12% vs. -0.3%), but MdAPE did not (18% vs. 15%). No difference in heart rate, MAP or BIS was found. Compared with the other models, the Eleveld propofol PK model (patients) showed the best prediction performance. CONCLUSIONS: When an accurate population-based PK model was used for propofol TCI, Bayesian adaption of the model improved bias but not precision. CLINICAL TRIAL REGISTRATION: Dutch Trial Registry NTR4518.

Pharmacokinetic models for propofol--defining and illuminating the devil in the detail.

The recently introduced open-target-controlled infusion (TCI) systems can be programmed with any pharmacokinetic model, and allow either plasma- or effect-site targeting. With effect-site targeting the goal is to achieve a user-defined target effect-site concentration as rapidly as possible, by manipulating the plasma concentration around the target. Currently systems are pre-programmed with the Marsh and Schnider pharmacokinetic models for propofol. The former is an adapted version of the Gepts model, in which the rate constants are fixed, whereas compartment volumes and clearances are weight proportional. The Schnider model was developed during combined pharmacokinetic-pharmacodynamic modelling studies. It has fixed values for V1, V3, k(13), and k(31), adjusts V2, k(12), and k(21) for age, and adjusts k(10) according to total weight, lean body mass (LBM), and height. In plasma targeting mode, the small, fixed V1 results in very small initial doses on starting the system or on increasing the target concentration in comparison with the Marsh model. The Schnider model should thus always be used in effect-site targeting mode, in which larger initial doses are administered, albeit still smaller than for the Marsh model. Users of the Schnider model should be aware that in the morbidly obese the LBM equation can generate paradoxical values resulting in excessive increases in maintenance infusion rates. Finally, the two currently available open TCI systems implement different methods of effect-site targeting for the Schnider model, and in a small subset of patients the induction doses generated by the two methods can differ significantly.

Simulated drug administration: an emerging tool for teaching clinical pharmacology during anesthesiology training.

A thorough understanding of the dose-response relationship is required for optimizing the efficacy of anesthetics while minimizing adverse drug effects. Nowadays, except for the inhaled anesthetics (for which end-tidal concentrations can be measured online), most of the drugs used in clinical anesthesia are administered using standard dosing guidelines, without giving due consideration to their pharmacokinetics and dynamics in guiding their administration. Various studies have found that introducing pharmacokinetics and pharmacodynamics as part of the inputs in clinical anesthesiology could lead to better patient care. With this in mind, it is extremely important that clinicians understand and apply the principles of clinical pharmacology that determine the time course of a drug's disposition and effect. Clinical pharmacology is one of the most challenging topics to teach in anesthesiology. The development of simulators to illustrate the time course of a drug's disposition and effect provides online visualization of pharmacokinetic-pharmacodynamic information during the clinical use of anesthetics. The aim of this review is to discuss the importance of simulation as a clinical pharmacology teaching tool for trainees in anesthesiology.

Feasibility study for the administration of remifentanil based on the difference between response entropy and state entropy.

BACKGROUND: Facial electromyography (FEMG) may have utility in the assessment of nociception during surgery. The difference between state entropy (SE) and response entropy (RE) is an indirect measure of FEMG. This study assesses an automated algorithm for remifentanil administration that is based on maintaining an entropy difference (ED) that is less than an upper boundary condition and greater than a lower boundary condition. METHODS: The algorithm was constructed with a development set (n = 40), and then automated and studied with a validation set (n = 20) of patients undergoing anterior cruciate ligament repair. The percentage of time that the ED was maintained between the two boundary conditions was determined. Remifentanil and propofol predicted effect-site concentrations (Ce) were determined at surgical milestones and, after drug discontinuation, the time to response to verbal stimulation and orientation was measured. RESULTS: The median (25th-75th percentile) per cent of time that the ED was recorded between the boundary conditions was 99.3% (98.1-99.8%). Predicted propofol (microg ml(-1)) and remifentanil (ng ml(-1)) Ce (sd), respectively, were 3.5 and 4.0 at induction, 1.9 (0.8) and 7.2 (3.7) at the end of surgery, and 1.1 (0.5) and 3.2 (2.2) at eye opening. The median time to eye opening and orientation was 3.8 and 6.8 min, respectively. CONCLUSION: This feasibility study supports the concept that remifentanil may be delivered using an algorithm that maintains the difference between SE and RE between the upper and lower boundary condition.

Predictive performance of the Domino, Hijazi, and Clements models during low-dose target-controlled ketamine infusions in healthy volunteers.

BACKGROUND: Healthy volunteers received low-dose target-controlled infusions (TCI) of ketamine controlled by the Domino model while cognitive function tests and functional neuroimaging were performed. The aim of the current study was to assess the predictive performance of the Domino model during these studies, and compare it with that of three other ketamine models. METHODS: Fifty-eight volunteers received ketamine administered by a TCI device on one or more occasions at target concentrations of either 50, 100, or 200 ng ml-1. At each target concentration, two or three venous blood samples were withdrawn during infusion, with a further sample after the infusion ended. Ketamine assays were performed by gas chromatography. The plasma concentration time courses predicted by the Hijazi, Clements 125, and Clements 250 models were calculated retrospectively, and the predictive performance of each of the models was assessed using Varvel methodology. RESULTS: For the Domino model, bias, inaccuracy, wobble, and divergence were - 2.7%, 33.9%, 24.2%, and 0.1463% h-1, respectively. There was a systematic increase in performance error over time. The Clements 250 model performed best by all criteria, whereas the Hijazi model performed least well by all criteria except for bias. CONCLUSIONS: Performance of the Domino model during control of low-dose ketamine infusions was sub-optimal. The Clements 250 model may be a better model for controlling low-dose TCI ketamine administration.

Comparison of closed-loop controlled administration of propofol using Bispectral Index as the controlled variable versus "standard practice" controlled administration.

BACKGROUND: This report describes a new closed-loop control system for propofol that uses the Bispectral Index (BIS) as the controlled variable in a patient-individualized, adaptive, model-based control system, and compares this system with manually controlled administration of propofol using hemodynamic and somatic changes to guide anesthesia. METHODS: Twenty female patients, American Society of Anesthesiologists physical status I or II, who were scheduled for gynecologic laparotomy were included to receive propofolremifentanil anesthesia. In group I, propofol was titrated using a BIS-guided, model-based, closed-loop system. The BIS target was set at 50. In group II, propofol was titrated using classical hemodynamic signs of (in)adequate anesthesia. Performance of control during induction and maintenance of anesthesia were compared between both groups using BIS as the controlled variable in group I and the reference variable in group II, and, conversely, the systolic blood pressure as the controlled variable in group II and the reference variable in group I. At the end of anesthesia, recovery profiles between groups were compared. RESULTS: Although patients undergoing manual induction of anesthesia in group II at 300 ml/h reached a BIS level of 50 faster than patients undergoing open-loop, computer-controlled induction in group I, manual induction caused a more pronounced initial overshoot of the BIS target. This resulted in a more pronounced decrease in blood pressure in group II. During the maintenance phase, better control of BIS and systolic blood pressure was found in group I compared with group II. Recovery was faster in group I. CONCLUSION: A closed-loop system for propofol administration using the BIS as a controlled variable together with a model-based controller is clinically acceptable during general anesthesia.

Comparison of plasma compartment versus two methods for effect compartment--controlled target-controlled infusion for propofol.

BACKGROUND: Target-controlled infusion (TCI) systems can control the concentration in the plasma or at the site of drug effect. A TCI system that targets the effect site should be able to accurately predict the time course of drug effect. The authors tested this by comparing the performance of three control algorithms: plasmacontrol TCI versus two algorithms for effect-site control TCI. METHODS: One-hundred twenty healthy women patients received propofol via TCI for 12-min at a target concentration of 5.4 microg/ml. In all three groups, the plasma concentrations were computed using pharmacokinetics previously reported. In group I, the TCI device controlled the plasma concentration. In groups II and III, the TCI device controlled the effect-site concentration. In group II, the effect site was computed using a half-life for plasma effect-site equilibration (t1/2k(eo)) of 3.5 min. In group III, plasma effect-site equilibration rate constant (k(eo)) was computed to yield a time to peak effect of 1.6 min after bolus injection, yielding a t1/2keo of 34 s. the time course of propofol was measured using the bispectral index. Blood pressure, ventilation, and time of loss of consciousness were measured. RESULTS: The time course of propofol drug effect, as measured by the bispectral index, was best predicted in group III. Targeting the effect-site concentration shortened the time to loss of consciousness compared with the targeting plasma concentration without causing hypotension. The incidence of apnea was less in group III than in group II. CONCLUSION: Effect compartment-controlled TCI can be safely applied in clinical practice. A biophase model combining the Marsh kinetics and a time to peak effect of 1.6 min accurately predicted the time course of propofol drug effect.

Closed-loop controlled administration of propofol using bispectral analysis.

Ten patients, undergoing elective orthopaedic surgery under spinal anaesthesia, were sedated with propofol using a closed-loop feedback control system. The bispectral index (BIS), a new processed EEG parameter, was used as control variable. Propofol administration was controlled by a patient individualised adaptive model-based controller incorporating target-controlled infusion technology combined with a pharmacokinetic-dynamic model. This feedback control system for propofol administration proved to be adequate and safe. BIS was found to be well suited as control variable.