Antimicrobial agents and chemotherapy
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Antimicrob. Agents Chemother. · Feb 2007
Moxifloxacin, ofloxacin, sparfloxacin, and ciprofloxacin against Mycobacterium tuberculosis: evaluation of in vitro and pharmacodynamic indices that best predict in vivo efficacy.
Members of the fluoroquinolone class are being actively evaluated for inclusion in tuberculosis chemotherapy regimens, and we sought to determine the best in vitro and pharmacodynamic predictors of in vivo efficacy in mice. MICs for Mycobacterium tuberculosis H37Rv were 0.1 mg/liter (sparfloxacin [SPX]) and 0.5 mg/liter (moxifloxacin [MXF], ciprofloxacin [CIP], and ofloxacin [OFX]). The unbound fraction in the presence of murine serum was concentration dependent for MXF, OFX, SPX, and CIP. ⋯ The ratio of the AUC to the MIC was the pharmacodynamic parameter that best described the in vivo efficacy. In summary, a lack of intracellular killing predicted the lack of in vivo activity of CIP. The in vivo rank order for maximal efficacy of the three active fluoroquinolones was not clearly predicted by the in vitro assays, however.
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Antimicrob. Agents Chemother. · Feb 2007
Clinical prediction tool to identify patients with Pseudomonas aeruginosa respiratory tract infections at greatest risk for multidrug resistance.
Despite the increasing prevalence of multiple-drug-resistant (MDR) Pseudomonas aeruginosa, the factors predictive of MDR have not been extensively explored. We sought to examine factors predictive of MDR among patients with P. aeruginosa respiratory tract infections and to develop a tool to estimate the probability of MDR among such high-risk patients. This was a single-site, case-control study of patients with P. aeruginosa respiratory tract infections. ⋯ Within the final model, the predicted MDR P. aeruginosa likelihood was most dependent upon length of hospital stay, prior culture sample collection, and number of CART-derived prior antibiotic exposures. A history of a prolonged hospital stay and exposure to antipseudomonal antibiotics predicts multidrug resistance among patients with P. aeruginosa respiratory tract infections at our institution. Identifying these risk factors enabled us to develop a prediction tool to assess the risk of resistance and thus guide empirical antibiotic therapy.