Title |
How to optimise antimicrobial prescriptions in the Intensive Care Unit: principles of individualised dosing using pharmacokinetics and pharmacodynamics
|
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Published in |
International Journal of Antimicrobial Agents, January 2012
|
DOI | 10.1016/j.ijantimicag.2011.11.002 |
Pubmed ID | |
Authors |
Jason A. Roberts, Gavin M. Joynt, Gordon Y.S. Choi, Charles D. Gomersall, Jeffrey Lipman |
Abstract |
Optimising antimicrobial dosing for critically ill patients is highly challenging and when it is not achieved can lead to worse patient outcomes. To this end, use of dosing regimens recommended in package inserts from drug manufacturers is frequently insufficient to guide dosing in these patients appropriately. Whilst the effect of critical illness pathophysiology on the pharmacokinetic (PK) behaviour of antimicrobials can be profound, the variability of these changes between patients is still being quantified. The PK effects of hypoproteinaemia, organ dysfunction and the presence of augmented renal clearance may lead to plasma antimicrobial concentrations that are difficult to predict at the bedside, which may result in excess toxicity or suboptimal bacterial killing. This paper outlines the factors that affect pharmacokinetics in critically ill patients and how knowledge of these factors can increase the likelihood of achieving optimal antimicrobial plasma concentrations. In selected settings, we advocate individualised dosing of renally cleared antimicrobials using physiological data such as measured creatinine clearance and published non-renal clearance data. Where such data do not exist, therapeutic drug monitoring may be a useful alternative and has been associated with significant clinical benefits, although it is not currently widely available. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 1% |
Unknown | 87 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 14 | 16% |
Other | 13 | 15% |
Researcher | 13 | 15% |
Student > Master | 11 | 13% |
Student > Postgraduate | 7 | 8% |
Other | 16 | 18% |
Unknown | 14 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 48 | 55% |
Pharmacology, Toxicology and Pharmaceutical Science | 14 | 16% |
Immunology and Microbiology | 3 | 3% |
Computer Science | 2 | 2% |
Agricultural and Biological Sciences | 2 | 2% |
Other | 2 | 2% |
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