Vancomycin Pharmacokinetics Throughout Life: Results from a Pooled Population Analysis and Evaluation of Current Dosing Recommendations

Abstract Background and Objectives Uncertainty exists regarding the optimal dosing regimen for vancomycin in diferent patient populations, leading to a plethora of subgroup-specifc pharmacokinetic models and derived dosing regimens. We aimed to investigate whether a single model for vancomycin could be developed based on a broad dataset covering the extremes of patient characteristics. Furthermore, as a benchmark for current dosing recommendations, we evaluated and optimised the expected vancomycin exposure throughout life and for specifc patient subgroups. Methods A pooled population-pharmacokinetic model was built in NONMEM based on data from 14 diferent studies in diferent patient populations. Steady-state exposure was simulated and compared across patient subgr

Model to describe the degree of twitch potentiation during neuromuscular monitoring

Background Neuromuscular block is estimated by comparing the evoked peak twitch with a control value measured in the absence of neuromuscular block. In practice, this control value is often difficult to determine because repeated motor nerve stimulation 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. It is probably the result of myosin light chain phosphorylation creating an increased twitch force for a given amount of Ca2+ released at each action potential. Modelling of potentiation may improve studies of neuromuscular blocking agents using mechanomyography or accelerometry. Methods We used one- and two-exponential models to describe the degree of myosin light chain phosphorylation and associated twitch potentiation. These models were fitted to accelerographic twitch force measurements for various stimulation patterns and frequencies used in neuromuscular monitoring. Results Fitting a two-exponential model to twitch data for various stimulation rates and patterns provides better prediction than a one-exponential model. A one-exponential model performs poorly when the stimulation rate varies during measurement. Conclusions We conclude that a two-exponential model can predict the degree of twitch potentiation for the stimulation patterns and frequencies tested more accurately than a one-exponential model. However, if only one stimulation frequency is used, a one-exponential model can provide good accuracy. We illustrate that such a potentiation model can improve the ability of pharmacodynamic-pharmacokinetic neuromuscular block models to predict twitch response in the presence of a neuromuscular blocking agent

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

Drug interaction models are better predictors of tolerance/ response to noxious stimuli compared to individual measured parameters

Background and Goal of Study: This study continues the pursuit of the parameter with the best correlation to the probability of response to noxious stimuli of different intensity. We used data from a previous study by Heyse et al.1 on the interaction of sevoflurane and remifentanil to compare several parameters. Materials and Methods: After institutional review board approval, 40 adult patients were randomised to receive different combinations of sevoflurane (Sevo) and remifentanil (Remi) according to a criss-cross design. After reaching pseudo-steady state, the patients were assessed for tolerance of 'shake and shout' (SAS), tetanic stimulation (TET), insertion of laryngeal mask airway (LMA) and laryngoscopy (LAR). Bispectral index (BIS), state and response entropy (SE, RE), composite variability index (CVI) and surgical pleth index (SPI) were either recorded or computed from raw electroencephalographic and plethysmographic data retrospectively. Sevo and Remi concentrations were recorded. The combined potency of Sevo and Remi according to the fixed C50O hierarchical interaction model (U) and the noxious stimulation response index (NSRI) were the population-based predictors. We used the prediction probability (PK) to assess the performance of these parameters on the probability of response. Bootstrapping (n=1000) was used to produce 84%-confidence intervals of the PKs, with significance being achieved if the confidence intervals did not overlap (p <0.05). Results and Discussion: The parameter PKs per stimulus are summarised in Table 1.(Table Presented) The PK for U and NSRI were highest for all stimuli. Effect site concentrations of either Sevo or Remi alone were significantly worse predictors. BIS, SE, RE and CVI were significantly worse at predicting tolerance to the three painful stimuli, but similar to U and NSRI for SAS. SPI performed poorly overall. Conclusion: U and NSRI perform significantly better than EEG-derived parameters and single drug effect site concentrations in predicting tolerance to noxious stimuli. Therefore both U and NSRI could be useful parameters in anaesthetic practice

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 previously described pharmacokinetic-pharmacodynamic (PK-PD) and twitch potentiation models to simulate twitch data. Simulations consisted of twitch stabilization followed by a NMBA bolus close and subsequent onset and recovery front 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