Optimization of meropenem dosage in the critically ill population based on renal function
- 1.7k Downloads
To develop a meropenem population pharmacokinetic model in critically ill patients with particular focus on optimizing dosing regimens based on renal function.
Population pharmacokinetic analysis was performed with creatinine clearance (CrCl) and adjusted body weight to predict parameter estimates. Initial modeling was performed on 21 patients (55 samples). Validation was conducted with 12 samples from 5 randomly selected patients excluded from the original model. A 5,000-patient Monte Carlo simulation was used to ascertain optimal dosing regimens for three CrCl ranges.
Mean ± SD age, APACHE, and CrCl were 59.2 ± 16.8 years, 13.6 ± 7, and 78.3 ± 33.7 mL/min. Meropenem doses ranged from 0.5 g every 8 h (q8h)–2 g q8h as 0.5–3 h infusions. Median estimates for volume of the central compartment, K 12, and K 21 were 0.24 L/kg, 0.49 h−1, and 0.65 h−1, respectively. K 10 was described by the equation: K 10 = 0.3922 + 0.0025 × CrCl. Model bias and precision were −1.9 and 8.1 mg/L. R 2, bias, and precision for the validation were 93%, 1.1, and 2.6 mg/L. At minimum inhibitory concentrations (MICs) up to 8 mg/L, the probability of achieving 40% fT > MIC was 96, 90, and 61% for 3 h infusions of 2 g q8h, 1 g q8h, and 1 g q12h in patients with CrCl ≥50, 30–49, and 10–29, respectively. Target attainment was 75, 65, and 44% for these same dosing regimens as 0.5 h infusions.
This pharmacokinetic model is capable of accurately estimating meropenem concentrations in critically ill patients over a range of CrCl values. Compared with 0.5 h infusions, regimens employing prolonged infusions improved target attainment across all CrCl ranges.
KeywordsMeropenem Population pharmacokinetics Prolonged infusion Creatinine clearance Monte Carlo simulation
We would like to thank Christina Sutherland for her assistance with the analytical determination of meropenem and Aryun Kim, Pharm.D. for her assistance with collection of pharmacokinetic samples.
- 1.Merrem (2007) (Meropenem) package insert. AstraZeneca, WilmingtonGoogle Scholar
- 3.Clinical Laboratory Standard Institute (2008) Methods for dilution antimicrobial susceptibility tests for bacteria that grow aerobically; approved standard, 8th ed. CLSI Publication M07-A8, WayneGoogle Scholar
- 12.Roberts JA, Kirkpatrick CM, Roberts MS, Robertson TA, Dalley AJ, Lipman J (2009) 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 Antimicrob Chemother 64:142–150CrossRefPubMedGoogle Scholar
- 14.Leary RJ, Schumitzky A, Van Guilder M (2001) An adaptive grid, non-parametric approach to pharmacokinetic and dynamic (PK/PD) models. In: Proceedings, fouteenth IEEE symposium on computer-based medical systems. IEEE Computer Society, Bethesda, pp 389–394Google Scholar
- 17.Krueger WA, Bulitta J, Kinzig-Schippers M, Landersdorfer C, Holzgrabe U, Naber KG, Drusano GL, Sorgel F (2005) Evaluation by Monte Carlo simulation of the pharmacokinetics of two doses of meropenem administered intermittently or as a continuous infusion in healthy volunteers. Antimicrob Agents Chemother 49:1881–1889CrossRefPubMedGoogle Scholar
- 20.Thalhammer F, Traunmuller F, El Menyawi I, Frass M, Hollenstein UM, Locker GJ, Stoiser B, Staudinger T, Thalhammer-Scherrer R, Burgmann H (1999) Continuous infusion versus intermittent administration of meropenem in critically ill patients. J Antimicrob Chemother 43:523–527CrossRefPubMedGoogle Scholar
- 24.Bulik CC, Quintiliani Jr R, Samuel Pope J, Kuti JL, Nicolau DP (2009) Pharmacodynamics and tolerability of high-dose, prolonged infusion carbapenems in adults with cystic fibrosis—a review of 3 cases. Resp Med CME E pubGoogle Scholar