Literature DB >> 8431022

Comparison of population pharmacokinetic models for gentamicin in spinal cord-injured and able-bodied patients.

T M Gilman1, S R Brunnemann, J L Segal.   

Abstract

Population pharmacokinetic models for gentamicin were developed by using data obtained from 29 spinal cord-injured patients and 11 able-bodied control patients. With a one-compartment model, the population parameters were clearance (CL), volume of distribution (V), and their associated variances. Parameter estimates were found by using the computer program NPEM and by the standard two-stage (STS) method. NPEM uses a nonparametric approach incorporating the expectation maximization algorithm to evaluate a joint probability density function at 900 intersections over a bivariate grid. In contrast, the STS method requires conventional assumptions of normality for the underlying distributions. For NPEM, the mean CL was 97.6 ml/h/kg of body weight (coefficient of variation, 33.0% in the spinal cord-injured patients and 67.8 ml/h/kg +/- 28.2% in the able-bodied patients; the mean V was 0.31 liter/kg +/- 32.3% in the spinal cord-injured patients and 0.23 liter/kg +/- 15.8% in the able-bodied patients. For STS, the mean CL was 101.0 ml/h/kg +/- 37.5% in the spinal cord-injured patients and 65.0 ml/h/kg +/- 33.8% in the able-bodied patients; the mean V was 0.29 liter/kg +/- 34.0% in the spinal cord-injured patients and 0.21 liter/kg +/- 21.0% in the able-bodied patients. Although the means and variances found by NPEM and the STS method were similar, the NPEM analysis revealed that the distributions of CL and V, even after they were linked to weight, were positively skewed and kurtotic. The cumulative distribution functions for CL (P < 0.001) and V (P < 0.001) in spinal cord-injured patients were different from those in able-bodied patients. Unique population models are required for the initial dosage selection for spinal cord-injured patients. Future approaches for developing population models should allow the linkage of structural parameters to multiple patient covariates.

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Year:  1993        PMID: 8431022      PMCID: PMC187611          DOI: 10.1128/AAC.37.1.93

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  19 in total

1.  Body composition in quadriplegic patients.

Authors:  H M Shizgal; A Roza; B Leduc; G Drouin; J G Villemure; C Yaffe
Journal:  JPEN J Parenter Enteral Nutr       Date:  1986 Jul-Aug       Impact factor: 4.016

2.  [The nervous control of peripheral venous constriction at the beginning of exercise. Comparative study in normal man and in paraplegia due to section of the dorsal spinal cord].

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Journal:  Pathol Biol (Paris)       Date:  1971-01

3.  Factors affecting aminoglycoside disposition: effects of circadian rhythm and dietary protein intake on gentamicin pharmacokinetics.

Authors:  C J Dickson; M S Schwartzman; J S Bertino
Journal:  Clin Pharmacol Ther       Date:  1986-03       Impact factor: 6.875

4.  Alternative approaches to estimation of population pharmacokinetic parameters: comparison with the nonlinear mixed-effect model.

Authors:  J L Steimer; A Mallet; J L Golmard; J F Boisvieux
Journal:  Drug Metab Rev       Date:  1984       Impact factor: 4.518

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Authors:  S L Beal; L B Sheiner
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6.  Population pharmacokinetics of gentamicin. Use of the nonparametric expectation maximisation (NPEM) algorithm.

Authors:  D F Kisor; S M Watling; B J Zarowitz; R W Jelliffe
Journal:  Clin Pharmacokinet       Date:  1992-07       Impact factor: 6.447

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Journal:  Clin Pharmacokinet       Date:  1986 Sep-Oct       Impact factor: 6.447

8.  A simple method for the estimation of glomerular filtration rate by gentamicin pharmacokinetics during routine drug monitoring in the newborn.

Authors:  G Koren; A James; M Perlman
Journal:  Clin Pharmacol Ther       Date:  1985-12       Impact factor: 6.875

9.  The population approach to pharmacokinetic data analysis: rationale and standard data analysis methods.

Authors:  L B Sheiner
Journal:  Drug Metab Rev       Date:  1984       Impact factor: 4.518

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Authors:  J L Segal; D R Gray; S K Gordon; I M Eltorai; F Khonsari; J Patel
Journal:  Paraplegia       Date:  1985-02
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  4 in total

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Authors:  Carla C Medalha; Fernanda S Polesel; Victor Hugo Pereira da Silva; Renato Almeida Martins; Renan Pozzi; Daniel A Ribeiro
Journal:  Cell Mol Neurobiol       Date:  2012-04-03       Impact factor: 5.046

2.  Correlation of the pharmacokinetic parameters of amikacin and ceftazidime.

Authors:  Duangchit Panomvana; Sam-Ang Kiatjaroensin; Danabhand Phiboonbanakit
Journal:  Clin Pharmacokinet       Date:  2007       Impact factor: 6.447

3.  Comparison of aminoglycoside pharmacokinetics in Asian, Hispanic, and Caucasian patients by using population pharmacokinetic methods.

Authors:  S S Jhee; J P Burm; M A Gill
Journal:  Antimicrob Agents Chemother       Date:  1994-09       Impact factor: 5.191

4.  Scaling clearance in paediatric pharmacokinetics: All models are wrong, which are useful?

Authors:  Eva Germovsek; Charlotte I S Barker; Mike Sharland; Joseph F Standing
Journal:  Br J Clin Pharmacol       Date:  2016-12-02       Impact factor: 4.335

  4 in total

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