MIC-based interspecies prediction of the antimicrobial effects of ciprofloxacin on bacteria of different susceptibilities in an in vitro dynamic model - PubMed (original) (raw)

MIC-based interspecies prediction of the antimicrobial effects of ciprofloxacin on bacteria of different susceptibilities in an in vitro dynamic model

A A Firsov et al. Antimicrob Agents Chemother. 1998 Nov.

Abstract

Multiple predictors of fluoroquinolone antimicrobial effects (AMEs) are not usually examined simultaneously in most studies. To compare the predictive potentials of the area under the concentration-time curve (AUC)-to-MIC ratio (AUC/MIC), the AUC above MIC (AUCeff), and the time above MIC (Teff), the kinetics of killing and regrowth of four bacterial strains exposed to monoexponentially decreasing concentrations of ciprofloxacin were studied in an in vitro dynamic model. The MICs of ciprofloxacin for clinical isolates of Staphylococcus aureus, Escherichia coli 11775 (I) and 204 (II), and Pseudomonas aeruginosa were 0.6, 0.013, 0.08, and 0.15 microg/ml, respectively. The simulated values of AUC were designed to provide similar 1,000-fold (S. aureus, E. coli I, and P. aeruginosa) or 2, 000-fold (E. coli II) ranges of the AUC/MIC. In each case except for the highest AUC/MIC ratio, the observation periods included complete regrowth in the time-kill curve studies. The AME was expressed by its intensity, IE (the area between the control growth and time-kill and regrowth curves up to the point where the viable counts of regrowing bacteria are close to the maximum values observed without drug). For most AUC ranges the IE-AUC curves were fitted by an Emax (maximal effect) model, whereas the effects observed at very high AUCs were greater than those predicted by the model. The AUCs that produced 50% of maximal AME were proportional to the MICs for the strains studied, but maximal AMEs (IEmax) and the extent of sigmoidicity (s) were not related to the MIC. Both Teff and log AUC/MIC correlated well with IE (r2 = 0.98 in both cases) in a species-independent fashion. Unlike Teff or log AUC/MIC, a specific relationship between IE and log AUCeff was inherent in each strain. Although each IE and log AUCeff plot was fitted by linear regression (r2 = 0.97 to 0.99), these plots were not superimposed and therefore are bacterial species dependent. Thus, AUC/MIC and Teff were better predictors of ciprofloxacin's AME than AUCeff. This study suggests that optimal predictors of the AME produced by a given quinolone (intraquinolone predictors) may be established by examining its AMEs against bacteria of different susceptibilities. Teff was shown previously also to be the best interquinolone predictor, but unlike AUC/MIC, it cannot be used to compare different quinolones. AUC/MIC might be the best predictor of the AME in comparisons of different quinolones.

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Figures

FIG. 1

FIG. 1

Kinetics of killing and regrowth of different microorganisms exposed to ciprofloxacin. The simulated AUCs (in microgram · hours per milliliter) are indicated by the numbers at each curve. The dotted line indicates the low limit of accurate detection.

FIG. 2

FIG. 2

AUC-dependent antimicrobial effects of ciprofloxacin as described by equation 1. The systematically diverging points are crossed out.

FIG. 3

FIG. 3

Antimicrobial effects of ciprofloxacin related to the different predictors. ▵, S. aureus; ◊, E. coli I; □, E. coli II; ▿, P. aeruginosa.

FIG. 4

FIG. 4

Antimicrobial effects of ciprofloxacin expressed by _T_99% and Δlog _N_τ as related to the different predictors. The Δlog _N_τ values which were near the upper (Δlog _N_τ → 5) and lower (Δlog _N_τ → −6) limits of accurate detection and which were therefore ignored in the correlation analysis are indicated by filled symbols. ▵, S. aureus; ◊, E. coli I; □, E. coli II; ▿, P. aeruginosa.

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