Development and evaluation of a Bayesian pharmacokinetic estimator and optimal, sparse sampling strategies for ceftazidime

被引:17
作者
Kashuba, ADM
Ballow, CH
Forrest, A
机构
[1] SUNY BUFFALO, SCH PHARM, CTR CLIN PHARM RES, BUFFALO, NY 14260 USA
[2] MILLARD FILLMORE HOSP, CLIN PHARMACOKINET LAB, BUFFALO, NY 14209 USA
关键词
D O I
10.1128/AAC.40.8.1860
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Data were gathered during an activity-controlled trial in which seriously ill, elderly patients were randomized to receive intravenous ceftazidime or ciprofloxacin and for which adaptive feedback control of drug concentrations in plasma and activity profiles was prospectively performed, The adaptive feedback control algorithm for ceftazidime used an initial population model, a maximum a posteriori (MAP)-Bayesian pharmacokinetic parameter value estimator, and an optimal, sparse sampling strategy for ceftazidime that had been derived from data in the literature obtained from volunteers, Iterative two-stage population pharmacokinetic analysis was performed to develop an unbiased MAP-Bayesian estimator and updated optimal, sparse sampling strategies, The final median values of the population parameters were as follows: the volume of distribution of the central compartment was equal to 0.249 liter/kg, the volume of distribution of the peripheral compartment was equal to 0.173 liter/kg, the distributional clearance between the central and peripheral compartments was equal to 0.0251 liter/h/kg, the slope of the total clearance (CL) versus the creatinine clearance (CL(CR)) was equal to 0.000736 liter/h/kg of CL/1 ml/min/1.73 m(2) of CL(CR), and nonrenal clearance was equal to = 0.00527 liter/h/kg, Optimal sampling times were dependent on CL(CR); for CL(CR) of greater than or equal to 30 ml/min/1.73 m(2) the optimal sampling times were 0.583, 3.0, 7.0, and 16.0 h and, for CL(CR) of <30 ml/min/1.73 m(2), optimal sampling times were 0.583, 4.15, 11.5, and 24.0 h, The study demonstrates that because pharmacokinetic information from volunteers may often not be reflective of specialty populations such as critically ill elderly individuals, iterative two-stage population pharmacokinetic analysis, MAP-Bayesian parameter estimation, and optimal, sparse sampling strategy can be important tools in characterizing their pharmacokinetics.
引用
收藏
页码:1860 / 1865
页数:6
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