scholarly journals Population Pharmacokinetic Analysis of Piperacillin in Burn Patients

2014 ◽  
Vol 58 (7) ◽  
pp. 3744-3751 ◽  
Author(s):  
Sangil Jeon ◽  
Seunghoon Han ◽  
Jongtae Lee ◽  
Taegon Hong ◽  
Jeongki Paek ◽  
...  

ABSTRACTPiperacillin in combination with tazobactam, a β-lactamase inhibitor, is a commonly used intravenous antibiotic for the empirical treatment of infection in intensive care patients, including burn patients. The purpose of this study was to develop a population pharmacokinetic (PK) model for piperacillin in burn patients and to predict the probability of target attainment (PTA) using MICs and concentrations simulated from the PK model. Fifty burn patients treated with piperacillin-tazobactam were enrolled. Piperacillin-tazobactam was administered via infusion for approximately 30 min at a dose of 4.5 g (4 g piperacillin and 0.5 g tazobactam) every 8 h. Blood samples were collected just prior to and at 1, 2, 3, 4, and 6 h after the end of the infusion at steady state. The population PK model of piperacillin was developed using NONMEM. A two-compartment first-order elimination PK model was finally chosen. The covariates included were creatinine clearance (CLCR), day after burn injury (DAI), and sepsis. The final PK parameters were clearance (liters/h) (equal to 16.6 × [CLCR/132] + DAI × [−0.0874]), central volume (liters) (equal to 25.3 + 14.8 × sepsis [0 for the absence or 1 for the presence of sepsis]), peripheral volume (liters) (equal to 16.1), and intercompartmental clearance (liters/h) (equal to 0.636). The clearance and volume of piperacillin were higher than those reported in patients without burns, and the terminal half-life and PTA decreased with the increased CLCR. Our PK model suggests that higher daily doses or longer durations of infusion of piperacillin should be considered, especially for burn patients with a CLCRof ≥160 ml/min.

2015 ◽  
Vol 101 (1) ◽  
pp. e1.31-e1
Author(s):  
Nienke J Vet ◽  
Brenda CM de Winter ◽  
Saskia N de Wildt ◽  
Bart CH van der Nagel ◽  
Catherijne AJ Knibbe ◽  
...  

ObjectivesTo develop a population pharmacokinetic model of R-albuterol and S-albuterol for children suffering from status asthmaticus following continuous intravenous administration.MethodsAt the pediatric ICU 19 children suffering from severe status asthmaticus were treated using continuous intravenous albuterol in doses based on clinical symptoms (range 0.1–10 µg/kg/min). During therapy 111 blood samples were collected and analysed for R- and S-albuterol using a validated LC/MS-MS method. A population pharmacokinetic analysis was conducted using non-linear mixed effects modelling (NONMEM 7.2). Data was logarithmically transformed. Model selection criteria were decrease in objective function, diagnostic plots and NPDE. The covariates (range) analysed were bodyweight (7.8–70 kg), age (0.8–15.3 years), creatinine concentration (17–70 µmol/L), alanine transaminase (5–29 IU/L), and urea (1.6–4.8 mmol/L).ResultsA two-compartment model with separated clearance for R- (16.3 L/h) and S-albuterol (8.8 L/h) best described the data. Separated values for central volume of distribution (12.9 L), peripheral volume of distribution (45.2 L) and intercompartmental clearance (20.0 L/h) did not improve the model. Between-subject variability was described for clearance of R-albuterol (42%), clearance of S-albuterol (37%) and central volume of distribution (280%). Weight is a significant covariate using a power function. The exponent of the powerfunction was fixed at 0.75 for clearance and intercompartmental and at 1 for central and peripheral volume of distribution. Estimation of the exponent resulted in similar values and did not improve the model. No other covariates were identified.ConclusionThe population pharmacokinetics of R- and S-albuterol are described. This model can be used to evaluate the correlation between albuterol pharmacokinetics and effect in a population pharmacokinetic-pharmacodynamic analysis.


2009 ◽  
Vol 49 (10) ◽  
pp. 1142-1156 ◽  
Author(s):  
Peiming Ma ◽  
Bing-Bing Yang ◽  
Yow-Ming Wang ◽  
Mark Peterson ◽  
Adimoolam Narayanan ◽  
...  

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