<p>Cefuroxime is a renally eliminated antibiotic used against a variety of different bacterial infections. The pharmacokinetics (PK) for cefuroxime was studied in 97 hospitalized patients using population analysis. To be able to measure cefuroxime in human serum a new sensitive analytical method was developed using mass spectrometry detection. The method was validated and shown to be sensitive and selective. Cystatin C was found to be a better covariate for cefuroxime clearance compared to the traditionally used creatinine clearance (CLcr). This relation might be useful when designing dosing strategies for cefuroxime and other renally eliminated drugs. </p><p>The time-courses of the biomarkers C-reactive protein (CRP), serum amyloid A (SAA), interleukin-6 (IL-6) and body temperature were studied for the first 72 hours of cefuroxime treatment and was related to the duration of illness previous treatment with cefuroxime and to time to step-down of treatment. When duration of illness was short, CRP and SAA were showed increasing levels. None of the biomarkers could be used to differentiate between early or late step-down of therapy.</p><p>By use of known PK and pharmacodynamic (PD) principles, dosing strategies based on CLcr for cefuroxime were estimated using minimization of a risk function. The risk function was constructed with the aim to expose patients to cefuroxime concentration above minimum inhibitory concentration (MIC) for 50 % of the dosing interval and to minimize the amount of drug administered in excess to reach the aim. Based on evaluation using wild type MIC distributions for <i>Escherichia coli</i> and <i>Streptococcus pneumoniae</i> improved dosing strategies were selected.</p><p>In vitro experiments were performed exposing <i>Streptococcus pyogenes</i> to constant concentration of benzylpenicillin, cefuroxime, erythromycin, moxifloxacin or vancomycin. A semi-mechanistic PK/PD model characterizing the time-course of the antibacterial effect was developed using all data simultaneously. Internal validation showed the model being predictive and robust. </p>
Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:uu-6639 |
Date | January 2006 |
Creators | Viberg, Anders |
Publisher | Uppsala University, Division of Pharmacokinetics and Drug Therapy, Uppsala : Acta Universitatis Upsaliensis |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Doctoral thesis, comprehensive summary, text |
Relation | Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, 1651-6192 ; 29 |
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