The performance of a target-controlled infusion of propofol in combination with remifentanil: a clinical investigation with two propofol formulations

Measuring the accuracy of propofol target-controlled infusion (TCI) before and after surgery with major blood loss

Target-controlled infusion (TCI) is based on pharmacokinetic models designed to achieve a desired drug level in the blood. TCI's predictive accuracy of plasma propofol levels at the end of surgery with major blood loss has not been well established. This prospective observational study included adult patients (BMI 20-35 kg/m²) undergoing surgery with expected blood loss ≥ 1500 mL. The study was conducted with the Schnider TCI propofol model (Alaris PK Infusion Pump, CareFusion, Switzerland). Propofol levels were assessed in steady-state at the end of anaesthesia induction (T_initial) and before the end of surgery (T_final). Predicted propofol levels (C_TCI) were compared to measured levels (C_blood). Twenty-one patients were included. The median estimated blood loss was 1600 mL (IQR 1000-2300), and the median fluid balance at T_final was + 3200 mL (IQR 2320-4715). Heart rate, mean arterial blood pressure, and blood lactate did not differ significantly between T_initial and T_final. The median bispectral index (0-100) was 50 (IQR 42-54) and 49 (IQR 42-56) at the two respective time points. At T_initial, median C_TCI was 2.2 µmol/L (IQR 2-2.45) and C_blood was 2.0 µmol/L (bias 0.3 µmol/L, limits of agreement - 1.1 to 1.3, p = 0.33). C_TCI and C_blood at T_final were 2.0 µmol/L (IQR 1.6-2.2) and 1 µmol/L (IQR 0.8-1.4), respectively (bias 0.6 µmol/L, limits of agreement - 0.89 to 1.4, p < 0.0001). Propofol TCI allows clinically unproblematic conduct of general anaesthesia. In cases of major blood loss, the probability of propofol TCI overestimating plasma levels increases.Trial registration German Clinical Trials Register (DRKS; DRKS00009312).

Population pharmacokinetic-pharmacodynamic model of propofol in adolescents undergoing scoliosis surgery with intraoperative wake-up test: a study using Bispectral index and composite auditory evoked potentials as pharmacodynamic endpoints

BACKGROUND

In adolescents limited data are available on the pharmacokinetics (PK) and pharmacodynamics (PD) of propofol. In this study we derived a PK-PD model for propofol in adolescents undergoing idiopathic scoliosis surgery with an intraoperative wake-up test with reinduction of anesthesia using both Bispectral Index (BIS) and composite A-line ARX index (cAAI) as endpoints.

METHODS

Fourteen adolescents (9.8-20.1 years) were evaluated during standardized propofol-remifentanil anesthesia for idiopathic scoliosis surgery with an intraoperative wake-up test with reinduction of anesthesia. BIS and cAAI were continuously measured and blood samples collected. A propofol PKPD model was developed using NONMEM.

RESULTS

The time courses of propofol concentrations, BIS and cAAI values during anesthesia, intra-operative wakeup and reduction of anesthesia were best described by a two-compartment PK model linked to an inhibitory sigmoidal Emax PD model. For the sigmoidal Emax model, the propofol concentration at half maximum effect (EC₅₀) was 3.51 and 2.14 mg/L and Hill coefficient 1.43 and 6.85 for BIS and cAAI, respectively. The delay in PD effect in relation to plasma concentration was best described by a two compartment effect-site model with a ke_o of 0.102 min^- 1, ke₁₂ of 0.121 min^- 1 and ke₂₁ of 0.172 min^- 1.

CONCLUSIONS

A population PKPD model for propofol in adolescents was developed that successfully described the time course of propofol concentration, BIS and cAAI in individuals upon undergoing scoliosis surgery with intraoperative wake-up test and reinduction of anesthesia. Large differences were demonstrated between both monitors. This may imply that BIS and cAAI measure fundamentally different endpoints in the brain.

Clinical Pharmacokinetics and Pharmacodynamics of Propofol

Propofol is an intravenous hypnotic drug that is used for induction and maintenance of sedation and general anaesthesia. It exerts its effects through potentiation of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) at the GABAA receptor, and has gained widespread use due to its favourable drug effect profile. The main adverse effects are disturbances in cardiopulmonary physiology. Due to its narrow therapeutic margin, propofol should only be administered by practitioners trained and experienced in providing general anaesthesia. Many pharmacokinetic (PK) and pharmacodynamic (PD) models for propofol exist. Some are used to inform drug dosing guidelines, and some are also implemented in so-called target-controlled infusion devices, to calculate the infusion rates required for user-defined target plasma or effect-site concentrations. Most of the models were designed for use in a specific and well-defined patient category. However, models applicable in a more general population have recently been developed and published. The most recent example is the general purpose propofol model developed by Eleveld and colleagues. Retrospective predictive performance evaluations show that this model performs as well as, or even better than, PK models developed for specific populations, such as adults, children or the obese; however, prospective evaluation of the model is still required. Propofol undergoes extensive PK and PD interactions with both other hypnotic drugs and opioids. PD interactions are the most clinically significant, and, with other hypnotics, tend to be additive, whereas interactions with opioids tend to be highly synergistic. Response surface modelling provides a tool to gain understanding and explore these complex interactions. Visual displays illustrating the effect of these interactions in real time can aid clinicians in optimal drug dosing while minimizing adverse effects. In this review, we provide an overview of the PK and PD of propofol in order to refresh readers' knowledge of its clinical applications, while discussing the main avenues of research where significant recent advances have been made.

Pharmacokinetic and pharmacodynamic interactions in anaesthesia. A review of current knowledge and how it can be used to optimize anaesthetic drug administration

This review describes the basics of pharmacokinetic and pharmacodynamic drug interactions and methodological points of particular interest when designing drug interaction studies. It also provides an overview of the available literature concerning interactions, with emphasis on graphic representation of interactions using isoboles and response surface models. It gives examples on how to transform this knowledge into clinically and educationally applicable (bedside) tools.

Comparison of propofol pharmacokinetic and pharmacodynamic models for awake craniotomy: A prospective observational study

BACKGROUND

Anaesthesia for awake craniotomy aims for an unconscious patient at the beginning and end of surgery but a rapidly awakening and responsive patient during the awake period. Therefore, an accurate pharmacokinetic/pharmacodynamic (PK/PD) model for propofol is required to tailor depth of anaesthesia.

OBJECTIVE

To compare the predictive performances of the Marsh and the Schnider PK/PD models during awake craniotomy.

DESIGN

A prospective observational study.

SETTING

Single university hospital from February 2009 to May 2010.

PATIENTS

Twelve patients undergoing elective awake craniotomy for resection of brain tumour or epileptogenic areas.

INTERVENTION

Arterial blood samples were drawn at intervals and the propofol plasma concentration was determined.

MAIN OUTCOME MEASURES

The prediction error, bias [median prediction error (MDPE)] and inaccuracy [median absolute prediction error (MDAPE)] of the Marsh and the Schnider models were calculated. The secondary endpoint was the prediction probability PK, by which changes in the propofol effect-site concentration (as derived from simultaneous PK/PD modelling) predicted changes in anaesthetic depth (measured by the bispectral index).

RESULTS

The Marsh model was associated with a significantly (P = 0.05) higher inaccuracy (MDAPE 28.9 ± 12.0%) than the Schnider model (MDAPE 21.5 ± 7.7%) and tended to reach a higher bias (MDPE Marsh -11.7 ± 14.3%, MDPE Schnider -5.4 ± 20.7%, P = 0.09). MDAPE was outside of accepted limits in six (Marsh model) and two (Schnider model) of 12 patients. The prediction probability was comparable between the Marsh (PK 0.798 ± 0.056) and the Schnider model (PK 0.787 ± 0.055), but after adjusting the models to each individual patient, the Schnider model achieved significantly higher prediction probabilities (PK 0.807 ± 0.056, P = 0.05).

CONCLUSION

When using the 'asleep-awake-asleep' anaesthetic technique during awake craniotomy, we advocate using the PK/PD model proposed by Schnider. Due to considerable interindividual variation, additional monitoring of anaesthetic depth is recommended.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT 01128465.

Performance of propofol target-controlled infusion models in the obese: pharmacokinetic and pharmacodynamic analysis

BACKGROUND

Obesity is associated with important physiologic changes that can potentially affect the pharmacokinetic (PK) and pharmacodynamic (PD) profile of anesthetic drugs. We designed this study to assess the predictive performance of 5 currently available propofol PK models in morbidly obese patients and to characterize the Bispectral Index (BIS) response in this population.

METHODS

Twenty obese patients (body mass index >35 kg/m), aged 20 to 60 years, scheduled for laparoscopic bariatric surgery, were studied. Anesthesia was administered using propofol by target-controlled infusion and remifentanil by manually controlled infusion. BIS data and propofol infusion schemes were recorded. Arterial blood samples to measure propofol were collected during induction, maintenance, and the first 2 postoperative hours. Median performance errors (MDPEs) and median absolute performance errors (MDAPEs) were calculated to measure model performance. A PKPD model was developed using NONMEM to characterize the propofol concentration-BIS dynamic relationship in the presence of remifentanil.

RESULTS

We studied 20 obese adults (mean weight: 106 kg, range: 85-141 kg; mean age: 33.7 years, range: 21-53 years; mean body mass index: 41.4 kg/m, range: 35-52 kg/m). We obtained 294 arterial samples and analyzed 1431 measured BIS values. When total body weight (TBW) was used as input of patient weight, the Eleveld allometric model showed the best (P < 0.0001) performance with MDPE = 18.2% and MDAPE = 27.5%. The 5 tested PK models, however, showed a tendency to underestimate propofol concentrations. The use of an adjusted body weight with the Schnider and Marsh models improved the performance of both models achieving the lowest predictive errors (MDPE = <10% and MDAPE = <25%; all P < 0.0001). A 3-compartment PK model linked to a sigmoidal inhibitory Emax PD model by a first-order rate constant (ke0) adequately described the propofol concentration-BIS data. A lag time parameter of 0.44 minutes (SE = 0.04 minutes) to account for the delay in BIS response improved the fit. A simulated effect-site target of 3.2 μg/mL (SE = 0.17 μg/mL) was estimated to obtain BIS of 50, in the presence of remifentanil, for a typical patient in our study.

CONCLUSIONS

The Eleveld allometric PK model proved to be superior to all other tested models using TBW. All models, however, showed a trend to underestimate propofol concentrations. The use of adjusted body weight instead of TBW with the traditional Schnider and Marsh models markedly improved their performance achieving the lowest predictive errors of all tested models. Our results suggest no relevant effect of obesity on both the time profile of BIS response and the propofol concentration-BIS relationship.

A general purpose pharmacokinetic model for propofol

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.

Population pharmacokinetics of olprinone in healthy male volunteers

BACKGROUND

Olprinone decreases the cardiac preload and/or afterload because of its vasodilatory effect and increases myocardial contractility by inhibiting phosphodiesterase III.

PURPOSE

The objective of this study was to characterize the population pharmacokinetics of olprinone after a single continuous infusion in healthy male volunteers.

METHODS

We used 500 plasma concentration data points collected from nine healthy male volunteers for the study. The population pharmacokinetic analysis was performed using the nonlinear mixed effect model (NONMEM®) software.

RESULTS

The time course of plasma concentration of olprinone was best described using a two-compartment model. The final pharmacokinetic parameters were total clearance (7.37 mL/minute/kg), distribution volume of the central compartment (134 mL/kg), intercompartmental clearance (7.75 mL/minute/kg), and distribution volume of the peripheral compartment (275 mL/kg). The interindividual variability in the total clearance was 12.4%, and the residual error variability (exponential and additive) were 22.2% and 0.129 (standard deviation). The final pharmacokinetic model was assessed using a bootstrap method and visual predictive check.

CONCLUSION

We developed a population pharmacokinetic model of olprinone in healthy male adults. The bootstrap method and visual predictive check showed that this model was appropriate. Our results might be used to develop the population pharmacokinetic model in patients.

Design and implementation of a closed-loop control system for infusion of propofol guided by bispectral index (BIS)

BACKGROUND

This study describes the design of a hypnosis closed-loop control system with propofol. The controller used a proportional-integral (PI) algorithm with the bispectral index (BIS) as the feedback signal. Our hypothesis was that a PI closed-loop control could be applied in clinical practice safely keeping the BIS within a pre-determined target range.

METHODS

The adjustment of the PI parameters was based on simulation. The procedure had three steps: obtaining a patient model using data from 12 patients, designing and adjusting the controller in simulation, and fine tuning the PI parameters in a pilot study (10 patients). The resulting controller was tested in 24 American Society of Anesthesiology (ASA) I-II patients. The controller directly decides the infusion rate of propofol, and no model is necessary in its online operation. The BIS target was set to 50. Remifentanil was used for analgesia.

RESULTS

We evaluated the efficiency and safety of the automatic feedback system. It worked properly in all the patients. The median performance error was -1.62, and the median absolute performance error was 11.03. Average propofol-normalized consumption was 5.3 ± 1.8 mg/kg/h. Mean percentage of BIS in the range 40-60 was 83%. Mean time to open eyes was 8 ± 4 min. Time to extubation was 9 ± 5 min. Hemodynamic adverse event or intraoperative awareness were not recorded.

CONCLUSIONS

The closed-loop system was able to maintain the BIS within an acceptable range of levels. The control of a propofol infusion guided by the BIS is feasible without hemodynamic instability in ASA I/II patients.

Cross-simulation between two pharmacokinetic models for the target-controlled infusion of propofol

BACKGROUND

We investigated how one pharmacokinetic (PK) model differed in prediction of plasma (C(p)) and effect-site concentration (C(eff)) using a reproducing simulation of target-controlled infusion (TCI) with another PK model of propofol.

METHODS

Sixty female patients were randomly assigned to TCI using Marsh PK (Group M) and TCI using Schnider PK (Group S) targeting 6.0 µg/ml of C(p) of propofol for induction of anesthesia, and loss of responsiveness (LOR) was evaluated. Total and separate cross-simulation were investigated using the 2 hr TCI data (Marsh TCI and Schnider TCI), and we investigated the reproduced predicted concentrations (MARSH(SCH) and SCHNIDER(MAR)) using the other model. The correlation of the difference with covariates, and the influence of the PK parameters on the difference of prediction were investigated.

RESULTS

Group M had a shorter time to LOR compared to Group S (P < 0.001), but C(eff) at LOR was not different between groups. Reproduced simulations showed different time courses of C(p). MARSH(SCH) predicted a higher concentration during the early phase, whereas SCHNIDER(MAR) was maintained at a higher concentration. Volume and clearance of the central compartment were relevant to the difference of prediction, respectively. Body weight correlated well with differences in prediction between models (R(sqr) = 0.9821, P < 0.001).

CONCLUSIONS

We compared two PK models to determine the different infusion behaviors during TCI, which resulted from the different parameter sets for each PK model.

Population pharmacokinetics of landiolol hydrochloride in healthy subjects

Landiolol hydrochloride is a newly developed cardioselective, ultra short-acting beta(1)-adrenergic receptor blocking agent used for perioperative arrhythmia control. The objective of this study was to characterize the population pharmacokinetics of landiolol hydrochloride in healthy male subjects. A total of 420 blood concentration data points collected from 47 healthy male subjects were used for the population pharmacokinetic analysis. NONMEM was used for population pharmacokinetic analysis. In addition, the final pharmacokinetic model was evaluated using a bootstrap method and a leave-one-out cross validation method. The concentration time course of landiolol hydrochloride was best described by a two-compartment model with lag time. The final parameters were total body clearance (CL: 36.6 mL/min/kg), distribution volume of the central compartment (V1: 101 mL/kg), inter-compartmental clearance (16.1 mL/min/kg), distribution volume of the peripheral compartment (55.6 mL/kg), and lag time (0.82 min). The inter-individual variability in the CL and V1 were 21.8% and 46.3%, respectively. The residual variability was 22.1%. Model evaluation by the two different methods indicated that the final model was robust and parameter estimates were reasonable. The population pharmacokinetic model for landiolol hydrochloride in healthy subjects was developed and was shown to be appropriate by both bootstrap and leave-one-out cross validation methods.

[Target-controlled infusion (TCI) - a concept with a future?: state-of-the-art, treatment recommendations and a look into the future]

Over the last 10 years the technique of target-controlled infusion (TCI) has substantially influenced the development and practice of intravenous anaesthesia. It opened the possibility of many new and exciting applications of perioperative anaesthetic care. More recent and current developments, such as open TCI (target-controlled infusion) and the availability of generic anaesthetic agents combined with modern infusion pumps, means that TCI can become a standard procedure in anaesthesia and is no longer just a research tool for specialists and enthusiasts. This review explains the fundamentals and applications of intravenous drug delivery by TCI and gives practice guidelines to successfully implement the technique into clinical practice. The aim is to provide a comprehensive reference based on clinically proven evidence.