Literature DB >> 27270281

Development and Evaluation of a Gentamicin Pharmacokinetic Model That Facilitates Opportunistic Gentamicin Therapeutic Drug Monitoring in Neonates and Infants.

Eva Germovsek1, Alison Kent2, Tuuli Metsvaht3, Irja Lutsar3, Nigel Klein4, Mark A Turner5, Mike Sharland2, Elisabet I Nielsen6, Paul T Heath2, Joseph F Standing4.   

Abstract

Trough gentamicin therapeutic drug monitoring (TDM) is time-consuming, disruptive to neonatal clinical care, and a patient safety issue. Bayesian models could allow TDM to be performed opportunistically at the time of routine blood tests. This study aimed to develop and prospectively evaluate a new gentamicin model and a novel Bayesian computer tool (neoGent) for TDM use in neonatal intensive care. We also evaluated model performance for predicting peak concentrations and the area under the concentration-time curve from time 0 h to time t h (AUC0- t). A pharmacokinetic meta-analysis was performed on pooled data from three studies (1,325 concentrations from 205 patients). A 3-compartment model was used with the following covariates: allometric weight scaling, postmenstrual and postnatal age, and serum creatinine concentration. Final parameter estimates (standard errors) were as follows: clearance, 6.2 (0.3) liters/h/70 kg of body weight; central volume (V), 26.5 (0.6) liters/70 kg; intercompartmental disposition (Q), 2.2 (0.3) liters/h/70 kg; peripheral volume V2, 21.2 (1.5) liters/70 kg; intercompartmental disposition (Q2), 0.3 (0.05) liters/h/70 kg; peripheral volume V3, 148 (52.0) liters/70 kg. The model's ability to predict trough concentrations from an opportunistic sample was evaluated in a prospective observational cohort study that included data from 163 patients and 483 concentrations collected in five hospitals. Unbiased trough predictions were obtained; the median (95% confidence interval [CI]) prediction error was 0.0004 (-1.07, 0.84) mg/liter. Results also showed that peaks and AUC0- t values could be predicted (from one randomly selected sample) with little bias but relative imprecision, with median (95% CI) prediction errors being 0.16 (-4.76, 5.01) mg/liter and 10.8 (-24.9, 62.2) mg · h/liter, respectively. neoGent was implemented in R/NONMEM and in the freely available TDMx software.
Copyright © 2016, American Society for Microbiology. All Rights Reserved.

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Year:  2016        PMID: 27270281      PMCID: PMC4958175          DOI: 10.1128/AAC.00577-16

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


  41 in total

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9.  Prioritising neonatal medicines research: UK Medicines for Children Research Network scoping survey.

Authors:  Mark A Turner; Sara Lewis; Daniel B Hawcutt; D Field
Journal:  BMC Pediatr       Date:  2009-08-12       Impact factor: 2.125

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4.  Scaling beta-lactam antimicrobial pharmacokinetics from early life to old age.

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5.  Revising Pediatric Vancomycin Dosing Accounting for Nephrotoxicity in a Pharmacokinetic-Pharmacodynamic Model.

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6.  Population pharmacokinetics and dose optimisation of colecalciferol in paediatric patients with chronic kidney disease.

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7.  IV and oral fosfomycin pharmacokinetics in neonates with suspected clinical sepsis.

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8.  External Evaluation of a Gentamicin Infant Population Pharmacokinetic Model Using Data from a National Electronic Health Record Database.

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Journal:  Antimicrob Agents Chemother       Date:  2018-08-27       Impact factor: 5.938

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

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Review 10.  Precision Dosing: Public Health Need, Proposed Framework, and Anticipated Impact.

Authors:  Daniel Gonzalez; Gauri G Rao; Stacy C Bailey; Kim L R Brouwer; Yanguang Cao; Daniel J Crona; Angela D M Kashuba; Craig R Lee; Kathryn Morbitzer; J Herbert Patterson; Tim Wiltshire; Jon Easter; Scott W Savage; J Robert Powell
Journal:  Clin Transl Sci       Date:  2017-08-10       Impact factor: 4.689

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