Evaluation of Empirical Dosing Regimens for Meropenem in Intensive Care Unit Patients Using Population Pharmacokinetic Modeling and Target Attainment Analysis

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Abstract

ABSTRACT

In the present study, population pharmacokinetic (PK) analysis was performed based on meropenem data from a prospective study conducted in 114 critically ill patients with a wide range of renal functions and various disease conditions. The final model was a one-compartment model with linear elimination, with creatinine clearance and continuous renal replacement therapy affecting clearance, and total bodyweight impacting the volume of distribution. Our model is a valuable addition to the existing meropenem population PK models, and it could be particularly useful during implementation of a therapeutic drug monitoring program combined with Bayesian forecasting. Based on the final model developed, comprehensive Monte Carlo simulations were performed to evaluate the probability of target attainment (PTA) of 16 different dosing regimens. Simulation results showed that 2 g administered every 8 h with 3-h prolonged infusion (PI) and 4 g/day by continuous infusion (CI) appear to be two empirical dosing regimens that are superior to many other regimens when both target attainment and potential toxicity are considered and renal function information is not available. Following a daily CI dose of 6 g or higher, more than 30% of the population with a creatinine clearance of <60 mL/min is predicted to have neurotoxicity. With the availability of institution- and/or unit-specific meropenem susceptibility patterns, as well as an individual patient’s renal function, our PTA results may represent useful references for physicians to make dosing decisions.

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DALI: defining antibiotic levels in intensive care unit patients: are current β-lactam antibiotic doses sufficient for critically ill patients?

Jason A Roberts, Sanjoy K Paul, Murat Akova … (2014)

Morbidity and mortality for critically ill patients with infections remains a global healthcare problem. We aimed to determine whether β-lactam antibiotic dosing in critically ill patients achieves concentrations associated with maximal activity and whether antibiotic concentrations affect patient outcome. This was a prospective, multinational pharmacokinetic point-prevalence study including 8 β-lactam antibiotics. Two blood samples were taken from each patient during a single dosing interval. The primary pharmacokinetic/pharmacodynamic targets were free antibiotic concentrations above the minimum inhibitory concentration (MIC) of the pathogen at both 50% (50% f T>MIC) and 100% (100% f T>MIC) of the dosing interval. We used skewed logistic regression to describe the effect of antibiotic exposure on patient outcome. We included 384 patients (361 evaluable patients) across 68 hospitals. The median age was 61 (interquartile range [IQR], 48-73) years, the median Acute Physiology and Chronic Health Evaluation II score was 18 (IQR, 14-24), and 65% of patients were male. Of the 248 patients treated for infection, 16% did not achieve 50% f T>MIC and these patients were 32% less likely to have a positive clinical outcome (odds ratio [OR], 0.68; P = .009). Positive clinical outcome was associated with increasing 50% f T>MIC and 100% f T>MIC ratios (OR, 1.02 and 1.56, respectively; P < .03), with significant interaction with sickness severity status. Infected critically ill patients may have adverse outcomes as a result of inadeqaute antibiotic exposure; a paradigm change to more personalized antibiotic dosing may be necessary to improve outcomes for these most seriously ill patients.

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Meropenem dosing in critically ill patients with sepsis and without renal dysfunction: intermittent bolus versus continuous administration? Monte Carlo dosing simulations and subcutaneous tissue distribution.

J. Dalley, Craig S. Roberts, Henry T. Robertson … (2009)

To compare the plasma and subcutaneous tissue concentration-time profiles of meropenem administered by intermittent bolus dosing or continuous infusion to critically ill patients with sepsis and without renal dysfunction, and to use population pharmacokinetic modelling and Monte Carlo simulations to assess the cumulative fraction of response (CFR) against Gram-negative pathogens likely to be encountered in critical care units. We randomized 10 patients with sepsis to receive meropenem by intermittent bolus administration (n = 5; 1 g 8 hourly) or an equal dose administered by continuous infusion (n = 5). Serial subcutaneous tissue concentrations were determined using microdialysis and compared with plasma data for first-dose and steady-state pharmacokinetics. Population pharmacokinetic modelling of plasma data and Monte Carlo simulations were then undertaken with NONMEM. It was found that continuous infusion maintains higher median trough concentrations, in both plasma (intermittent bolus 0 versus infusion 7 mg/L) and subcutaneous tissue (0 versus 4 mg/L). All simulated intermittent bolus, extended and continuous infusion dosing achieved 100% of pharmacodynamic targets against most Gram-negative pathogens. Superior obtainment of pharmacodynamic targets was achieved using administration by extended or continuous infusion against less susceptible Pseudomonas aeruginosa and Acinetobacter species. This is the first study to compare the relative concentration-time data of bolus and continuous administration of meropenem at the subcutaneous tissue and plasma levels. We found that the administration of meropenem by continuous infusion maintains higher concentrations in subcutaneous tissue and plasma than by intermittent bolus dosing. Administration by extended or continuous infusion will achieve superior CFR against less-susceptible organisms in patients without renal dysfunction.

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Quantification of lean bodyweight.

Abigail N. Byrne, Susan Ash, Sarayut Janmahasatian … (2004)

Lean bodyweight (LBW) has been recommended for scaling drug doses. However, the current methods for predicting LBW are inconsistent at extremes of size and could be misleading with respect to interpreting weight-based regimens. The objective of the present study was to develop a semi-mechanistic model to predict fat-free mass (FFM) from subject characteristics in a population that includes extremes of size. FFM is considered to closely approximate LBW. There are several reference methods for assessing FFM, whereas there are no reference standards for LBW. A total of 373 patients (168 male, 205 female) were included in the study. These data arose from two populations. Population A (index dataset) contained anthropometric characteristics, FFM estimated by dual-energy x-ray absorptiometry (DXA - a reference method) and bioelectrical impedance analysis (BIA) data. Population B (test dataset) contained the same anthropometric measures and FFM data as population A, but excluded BIA data. The patients in population A had a wide range of age (18-82 years), bodyweight (40.7-216.5 kg) and BMI values (17.1-69.9 kg/m2). Patients in population B had BMI values of 18.7-38.4 kg/m2. A two-stage semi-mechanistic model to predict FFM was developed from the demographics from population A. For stage 1 a model was developed to predict impedance and for stage 2 a model that incorporated predicted impedance was used to predict FFM. These two models were combined to provide an overall model to predict FFM from patient characteristics. The developed model for FFM was externally evaluated by predicting into population B. The semi-mechanistic model to predict impedance incorporated sex, height and bodyweight. The developed model provides a good predictor of impedance for both males and females (r2 = 0.78, mean error [ME] = 2.30 x 10(-3), root mean square error [RMSE] = 51.56 [approximately 10% of mean]). The final model for FFM incorporated sex, height and bodyweight. The developed model for FFM provided good predictive performance for both males and females (r2 = 0.93, ME = -0.77, RMSE = 3.33 [approximately 6% of mean]). In addition, the model accurately predicted the FFM of subjects in population B (r2 = 0.85, ME = -0.04, RMSE = 4.39 [approximately 7% of mean]). A semi-mechanistic model has been developed to predict FFM (and therefore LBW) from easily accessible patient characteristics. This model has been prospectively evaluated and shown to have good predictive performance.