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    Predictability of Vancomycin Concentrations from Nine Approaches for Estimating Pharmacokinetic Parameters

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    Author
    Gillespie, David
    Affiliation
    College of Pharmacy, The University of Arizona
    Issue Date
    2005
    Keywords
    Vancomycin Concentrations
    Pharmacokinetic Parameters
    MeSH Subjects
    Vancomycin
    Advisor
    Murphy, John
    
    Metadata
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    Rights
    Copyright © is held by the author.
    Collection Information
    This item is part of the Pharmacy Student Research Projects collection, made available by the College of Pharmacy and the University Libraries at the University of Arizona. For more information about items in this collection, please contact Jennifer Martin, Librarian and Clinical Instructor, Pharmacy Practice and Science, jenmartin@email.arizona.edu.
    Publisher
    The University of Arizona.
    Abstract
    Objectives: Doses of vancomycin are frequently estimated using various predictor formulas aiming for trough concentrations between 5 and 15 mg/L and peak concentrations between 25 and 40 mg/L.1 There is however, some controversy about the relationship between vancomycin concentrations and therapeutic response. This project compares the ability of several methods to estimate serum concentrations of vancomycin. Methods: This project was a retrospective look at 243 patient records, the patients were given vancomycin and later had at least one concentration measured. Data collected while the patient was being treated was used in the nine predictor models to determine which model would best predict actual concentrations. The methods compared were Moellering, Matzke, Lake-Peterson, Rodvold, Abbott, Birt, Burton, Ambrose, and Bauer. Results: There were 188 patients included in the analysis, 97 males and 91 women. The method with the least bias (+ 1.0) was the Rodvold method using the actual body weight. None of the models were very precise, with most around 10 (high of 12.83, and a low of 9.35). The r- values for all the models were also low, none of the models had an r- value greater than 0.5. The Lake-Peterson method predicted within 20% and 50% the most often; the Ambrose method the least often within 50%, and both Ambrose and Bauer the least often within 20%. The Lake-Peterson method predicted concentrations within plus or minus 2.5 and 5.0 mg/L of measured concentrations most frequently. The Ambrose method predicted concentrations within plus or minus 2.5 mg/L of measured the least often; Burton and Rodvold the least often within 5.0 mg/L of measured. Implications: With the best model only accurate (defined as ± 20%) less than 25 percent of the time, there is too much error to make a good decision on dose and interval without the feedback of measured serum concentrations. The models may be a good starting point as which dose and interval to choose, but they are not a substitute for measuring steady state concentrations.
    Description
    Class of 2005 Abstract
    Collections
    Pharmacy Student Research Projects

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