Selected article for: "antibiotic exposure and study population"

Author: Liu, Jiajun; Neely, Michael; Lipman, Jeffrey; Sime, Fekade; Roberts, Jason A.; Kiel, Patrick J.; Avedissian, Sean N.; Rhodes, Nathaniel J.; Scheetz, Marc H.
Title: Development of Population and Bayesian Models for Applied Use in Patients Receiving Cefepime
  • Cord-id: kuwy7pbo
  • Document date: 2020_3_5
  • ID: kuwy7pbo
    Snippet: BACKGROUND AND OBJECTIVE: Understanding pharmacokinetic disposition of cefepime, a β-lactam antibiotic, is crucial for developing regimens to achieve optimal exposure and improved clinical outcomes. This study sought to develop and evaluate a unified population pharmacokinetic model in both pediatric and adult patients receiving cefepime treatment. METHODS: Multiple physiologically relevant models were fit to pediatric and adult subject data. To evaluate the final model performance, a withheld
    Document: BACKGROUND AND OBJECTIVE: Understanding pharmacokinetic disposition of cefepime, a β-lactam antibiotic, is crucial for developing regimens to achieve optimal exposure and improved clinical outcomes. This study sought to develop and evaluate a unified population pharmacokinetic model in both pediatric and adult patients receiving cefepime treatment. METHODS: Multiple physiologically relevant models were fit to pediatric and adult subject data. To evaluate the final model performance, a withheld group of 12 pediatric patients and two separate adult populations were assessed. RESULTS: Seventy subjects with a total of 604 cefepime concentrations were included in this study. All adults (n = 34) on average weighed 82.7 kg and displayed a mean creatinine clearance of 106.7 mL/min. All pediatric subjects (n = 36) had mean weight and creatinine clearance of 16.0 kg and 195.6 mL/min, respectively. A covariate-adjusted two-compartment model described the observed concentrations well (population model R(2), 87.0%; Bayesian model R(2), 96.5%). In the evaluation subsets, the model performed similarly well (population R(2), 84.0%; Bayesian R(2), 90.2%). CONCLUSION: The identified model serves well for population dosing and as a Bayesian prior for precision dosing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40262-020-00873-3) contains supplementary material, which is available to authorized users.

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