Towards precision dosing of vancomycin in critically ill patients: an evaluation of the predictive performance of pharmacometric models in ICU patients

  • C.B. Cunio
    Affiliations
    Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia

    School of Medical Sciences, University of New South Wales, Sydney, Australia
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  • D.W. Uster
    Affiliations
    Department of Clinical Pharmacy, Institute of Pharmacy, University of Hamburg, Hamburg, Germany
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  • J.E. Carland
    Affiliations
    Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia

    St Vincent's Clinical School, Univeristy of New South Wales, Sydney, Australia

    Centre of Applied Medical Research, St Vincent's Hospital, Sydney, Australia
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  • H. Buscher
    Affiliations
    St Vincent's Clinical School, Univeristy of New South Wales, Sydney, Australia

    Centre of Applied Medical Research, St Vincent's Hospital, Sydney, Australia

    Department of Intensive Care Medicine, St Vincent's Hospital, Sydney, Australia
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  • Z. Liu
    Affiliations
    Stats Central, University of New South Wales, Sydney, Australia
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  • J. Brett
    Affiliations
    Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia

    St Vincent's Clinical School, Univeristy of New South Wales, Sydney, Australia
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  • M. Stefani
    Affiliations
    Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia

    St Vincent's Clinical School, Univeristy of New South Wales, Sydney, Australia
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  • G.R.D. Jones
    Affiliations
    St Vincent's Clinical School, Univeristy of New South Wales, Sydney, Australia

    SydPath, St Vincent's Hospital, Sydney, Australia
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  • R.O. Day
    Affiliations
    Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia

    School of Medical Sciences, University of New South Wales, Sydney, Australia

    St Vincent's Clinical School, Univeristy of New South Wales, Sydney, Australia

    Centre of Applied Medical Research, St Vincent's Hospital, Sydney, Australia
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  • S.G. Wicha
    Affiliations
    Department of Clinical Pharmacy, Institute of Pharmacy, University of Hamburg, Hamburg, Germany
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  • S.L. Stocker
    Correspondence
    Corresponding author. Sophie Stocker, Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia.
    Affiliations
    Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia

    St Vincent's Clinical School, Univeristy of New South Wales, Sydney, Australia

    Centre of Applied Medical Research, St Vincent's Hospital, Sydney, Australia
    Search for articles by this author

      Abstract

      Objectives

      Vancomycin dose recommendations depend on population pharmacokinetic models. These models have not been adequately assessed in critically ill patients, who exhibit large pharmacokinetic variability. This study evaluated model predictive performance in intensive care unit (ICU) patients and identified factors influencing model performance.

      Methods

      Retrospective data from ICU adult patients administered vancomycin were used to evaluate model performance to predict serum concentrations a priori (no observed concentrations included) or with Bayesian forecasting (using concentration data). Predictive performance was determined using relative bias (rBias, bias) and relative root mean squared error (rRMSE, precision). Models were considered clinically acceptable if rBias was between ±20% and 95% confidence intervals included zero. Models were compared with rRMSE; no threshold was used. The influence of clinical factors on model performance was assessed with multiple linear regression.

      Results

      Data from 82 patients were used to evaluate 12 vancomycin models. The Goti model was the only clinically acceptable model with both a priori (rBias 3.4%) and Bayesian forecasting (rBias 1.5%) approaches. Bayesian forecasting was superior to a priori prediction, improving with the use of more recent concentrations. Four models were clinically acceptable with Bayesian forecasting. Renal replacement therapy status (p < 0.001) and sex (p = 0.007) significantly influenced the performance of the Goti model.

      Conclusions

      The Goti, Llopis and Roberts models are clinically appropriate to inform vancomycin dosing in critically ill patients. Implementing the Goti model in dose prediction software could streamline dosing across both ICU and non-ICU patients, considering it is also the most accurate model in non-ICU patients.

      Keywords

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