OBJECTIVES: The study aimed to characterize the pharmacokinetics (PK) of four β-lactams (piperacillin, ceftazidime, cefepime, and meropenem) in patients comedicated with amikacin (AMK), and to confirm the predictive performance of AMK data, obtained from therapeutic drug monitoring (TDM), on these PK, using a population modeling approach. DESIGN AND METHODS: Serum samples were collected in 88 critically ill septic patients. For each β-lactam, the covariate model was optimized using renal function. Furthermore, predictive performance of AMK concentrations and PK parameters was assessed on β-lactam PK. RESULTS: A two-compartment model with first-order elimination best fitted the β-lactam data. Results supported the superiority of AMK concentrations, over renal function and AMK PK parameters, to assess the β-lactam PK. CONCLUSION: The study confirmed the significant link between the exposure to AMK and to β-lactams, and presented population models able to guide β-lactam dosage adjustments using renal biomarkers or TDM-related aminoglycoside data.
OBJECTIVES: The study aimed to characterize the pharmacokinetics (PK) of four β-lactams (piperacillin, ceftazidime, cefepime, and meropenem) in patients comedicated with amikacin (AMK), and to confirm the predictive performance of AMK data, obtained from therapeutic drug monitoring (TDM), on these PK, using a population modeling approach. DESIGN AND METHODS: Serum samples were collected in 88 critically ill septicpatients. For each β-lactam, the covariate model was optimized using renal function. Furthermore, predictive performance of AMK concentrations and PK parameters was assessed on β-lactam PK. RESULTS: A two-compartment model with first-order elimination best fitted the β-lactam data. Results supported the superiority of AMK concentrations, over renal function and AMK PK parameters, to assess the β-lactam PK. CONCLUSION: The study confirmed the significant link between the exposure to AMK and to β-lactams, and presented population models able to guide β-lactam dosage adjustments using renal biomarkers or TDM-related aminoglycoside data.
Authors: Dagan O Lonsdale; Emma H Baker; Karin Kipper; Charlotte Barker; Barbara Philips; Andrew Rhodes; Mike Sharland; Joseph F Standing Journal: Br J Clin Pharmacol Date: 2018-11-26 Impact factor: 4.335
Authors: Evelyn Dhont; Tatjana Van Der Heggen; Annick De Jaeger; Johan Vande Walle; Peter De Paepe; Pieter A De Cock Journal: Pediatr Nephrol Date: 2018-10-29 Impact factor: 3.714
Authors: Yanfang Feng; Caspar J Hodiamont; Reinier M van Hest; Stanley Brul; Constance Schultsz; Benno H Ter Kuile Journal: PLoS One Date: 2016-02-12 Impact factor: 3.240
Authors: Annabel Werumeus Buning; Caspar J Hodiamont; Natalia M Lechner; Margriet Schokkin; Paul W G Elbers; Nicole P Juffermans; Ron A A Mathôt; Menno D de Jong; Reinier M van Hest Journal: Antibiotics (Basel) Date: 2021-05-21