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

Germovsek, Eva (author)
UCL, Inst Child Hlth, Inflammat Infect & Rheumatol Sect, London, England.
Kent, Alison (author)
St Georges Univ London, Inst Infect & Immun, Paediat Infect Dis Res Grp, London, England.
Metsvaht, Tuuli (author)
Univ Tartu, Dept Microbiol, Tartu, Estonia.
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Lutsar, Irja (author)
Univ Tartu, Dept Microbiol, Tartu, Estonia.
Klein, Nigel (author)
UCL, Inst Child Hlth, Inflammat Infect & Rheumatol Sect, London, England.
Turner, Mark A. (author)
Univ Liverpool, Inst Translat Med, Dept Womens & Childrens Hlth, Liverpool, Merseyside, England.
Sharland, Mike (author)
St Georges Univ London, Inst Infect & Immun, Paediat Infect Dis Res Grp, London, England.
Nielsen, Elisabet I. (author)
Uppsala universitet,Institutionen för farmaceutisk biovetenskap
Heath, Paul T. (author)
St Georges Univ London, Inst Infect & Immun, Paediat Infect Dis Res Grp, London, England.
Standing, Joseph F. (author)
UCL, Inst Child Hlth, Inflammat Infect & Rheumatol Sect, London, England.
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UCL, Inst Child Hlth, Inflammat Infect & Rheumatol Sect, London, England St Georges Univ London, Inst Infect & Immun, Paediat Infect Dis Res Grp, London, England. (creator_code:org_t)
2016
2016
English.
In: Antimicrobial Agents and Chemotherapy. - 0066-4804 .- 1098-6596. ; 60:8, s. 4869-4877
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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 (AUC(0-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 AUC(0-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 center dot h/liter, respectively. neoGent was implemented in R/NONMEM and in the freely available TDMx software.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Farmakologi och toxikologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Pharmacology and Toxicology (hsv//eng)

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