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Douglas J Eleveld

Publications and source records attributed to Douglas J Eleveld.

6 recordsLinked to original sources
PubMed2006

Performance of an iterative two-stage bayesian technique for population pharmacokinetic analysis of rich data sets.

PURPOSE: To test the suitability of an Iterative Two-Stage Bayesian (ITSB) technique for population pharmacokinetic analysis of rich data sets, and to compare ITSB with Standard Two-Stage (STS) analysis and nonlinear Mixed Effect Modeling (MEM). MATERIALS AND METHODS: Data from a clinical study with rapacuronium and data generated by Monte Carlo simulation were analyzed by an ITSB technique described in literature, with some modifications, by STS, and by MEM (using NONMEM). The results were evaluated by comparing the mean error (accuracy) and root mean squared error (precision) of the estimated parameter values, their interindividual standard deviation, correlation coefficients, and residual standard deviation. In addition, the influence of initial estimates, number of subjects, number of measurements, and level of residual error on the performance of ITSB were investigated. RESULTS: ITSB yielded best results, and provided precise and virtually unbiased estimates of the population parameter means, interindividual variability, and residual standard deviation. The accuracy and precision of STS was poor, whereas ITSB performed better than MEM. CONCLUSIONS: ITSB is a suitable technique for population pharmacokinetic analysis of rich data sets, and in the presented data set it is superior to STS and MEM.

Algorithms↗
PubMed2006

Twitch potentiation influences the time course of twitch depression in muscle relaxant studies: a pharmacokinetic-pharmacodynamic explanation.

The time course of twitch depression following neuromuscular blocking agent (NMBA) administration is influenced by the duration of control neuromuscular monitoring (twitch stabilization). The physiological mechanism for this interaction is not known. During twitch stabilization twitch response often increases to a plateau, this is known as twitch potentiation or the staircase phenomenon. Since twitch potentiation contributes to the observed twitch response it may also influence the time course of twitch depression following NMBA administration. Our objective was to estimate the degree that twitch potentiation influences the time course of twitch depression following NMBA administration under conditions typical for muscle relaxation studies. We used previousy described pharmacokinetic-pharmacodynamic (PK-PD) and twitch potentiation models to simulate twitch data. Simulations consisted of twitch stabilization followed by a NMBA bolus dose and subsequent onset and recovery from muscle relaxation. Twitch data were analyzed for onset and recovery characteristics and the results compared to clinical muscle relaxation studies in existing literature. We found that twitch potentiation likely plays a minor role in shortened onset time and increased duration of twitch depression observed with long periods of twitch stabilization.

Computer Simulation↗
PubMed2005

Improving pharmacokinetic-pharmacodynamic models of muscle relaxants using potentiation modelling.

Repeated motor nerve stimulation performed during neuromuscular monitoring enhances the evoked mechanical response of the corresponding muscle resulting in an increased twitch response. This is known as twitch potentiation or the staircase phenomenon. For neuromuscular modelling research twitch stabilisation techniques are often used to reduce the visible effect of potentiation, but such techniques are not always effective. Our objective was to model pharmacokinetic-pharmacodynamic (PK-PD) and twitch potentiation and to estimate neuromuscular block (NMB) in the presence of twitch potentiation. We combined a standard PK-PD model with a model describing the degree of twitch potentiation. The combined model was used to predict mechanomyographic twitch measurements and estimate NMB and twitch potentiation during muscle relaxation monitoring. Model parameters and prediction accuracy were compared to the standard PK-PD model with and without linear baseline correction. The PK-PD-potentiation model allows NMB to be estimated in the presence of twitch potentiation. It also accurately predicts data from twitch stabilisation, which is ignored with the standard PK-PD model. Compared to the standard PK-PD model, estimated PD parameters ec50 and gamma were found to be higher using the PK-PD-potentiation model. Compared to linear baseline correction, estimated PD parameters ke0 and ec50 were found to be higher. A PK-PD-potentiation model can estimate the degree of twitch potentiation and the degree of NMB during neuromuscular monitoring. This model leads to different PD parameter estimations than the standard PK-PD model however the differences are small enough to be unlikely to cause great concern among researchers.

Algorithms↗
PubMed2005

Evaluation of a closed-loop muscle relaxation control system.

Automatic muscle relaxation control may reduce anesthesiologists' workload freeing them for other patient care requirements. In this report we describe a muscle relaxation controller designed for routine clinical application using rocuronium and the train-of-four count. A muscle relaxation monitor (TOF Watch SX) was connected to a laptop computer running a controller algorithm program that communicates with a syringe pump to form a closed-loop muscle relaxation system. The control algorithm uses proportional-integral and lookup table components and is designed to avoid the usability restrictions of existing controllers. The controller is optimized using an objective method to avoid the uncertainties of ''hand-crafted'' controller algorithms. Controller target was train-of-four count 1 or 2 and controller performance was evaluated in 15 patients. During 39 hours of closed-loop control, 96.1% of all twitches recorded were in the target range. Average rocuronium infusion rate was 0.36 mg.kg(-1).h(-1) (sd 0.18 mg.kg(-1).h(-1)). We show that the controller remains useful even in the presence of disturbances that can arise in routine clinical conditions. The muscle relaxation controller maintained the target train-of-four count values and may serve as a basis for the design of hardware and user interfaces for closed-loop muscle relaxation control in clinical conditions.

Aged↗
PubMed2003

A pharmacokinetic-pharmacodynamic model for neuromuscular blocking agents to predict train-of-four twitches.

The train-of-four (TOF) stimulation pattern consists of 4 stimuli (T1, T2, T3, and T4) at 2 Hz, and is used in daily anesthesiological practice to determine the degree of relaxation caused by muscle relaxants. At a surgical levels of relaxation the degree of relaxation can be estimated by counting the number of "measurable" or "visible" muscular reactions to the 4 stimuli in the TOF stimulation pattern (TOF count). During recovery relaxation can be estimated by calculating the TOF ratio (T4/T1). Bartkowski and Epstein described a pharmacokinetic-pharmacodynamic (PK-PD) model to predict TOF ratio by modifying and extending the PK-PD model as described by Sheiner to use a hypothetical distributed effect compartment described by a median equilibration rate constant and a dispersion parameter. We extended the Bartkowski and Epstein PK-PD model to simulate all four TOF twitches by including EC50 terms for T2 and T3. We fit this model to data from the pig and compared the results to fitted models using separate PD models for each TOF twitch (extended Sheiner model). The extended Bartkowski and Epstein model fit the twitch height data from all four TOF twitches better than the extended Sheiner model and has fewer parameters.

Anesthesia↗