OBJECTIVES: To determine the functional relationship between the density of bacteria and the pharmacodynamics of antibiotics, and the potential consequences of this inoculum effect on the microbiological course of antibiotic treatment of Staphylococcus aureus infections. METHODS: In vitro time-kill, MIC estimation and antibiotic bioassay experiments were performed with S. aureus ATCC 25923 to ascertain the functional relationship between rates of kill and the MICs of six classes of antibiotics and the density of bacteria exposed. The potential consequences of the observed inoculum effects on the microbiological course of antibiotic treatment are explored with a mathematical model. RESULTS: Modest or substantial inoculum effects on efficacy were observed for all six antibiotics studied, such as density-dependent declines in the rate and extent of antibiotic-mediated killing and increases in MIC. Although these measures of antibiotic efficacy declined with inoculum, this density effect did not increase monotonically. At higher densities, the rate of kill of ciprofloxacin and oxacillin declined with the antibiotic concentration. For daptomycin and vancomycin, much of this inoculum effect is due to density-dependent reductions in the effective concentration of the antibiotic. For the other four antibiotics, this density effect is primarily associated with a decrease in per-cell antibiotic concentration. With parameters in the range estimated, our mathematical model predicts that the course of antibiotic treatment can be affected by cell density; treatment protocols based on conventional (density-independent) MICs can fail to clear higher density infections. CONCLUSIONS: The MICs used for pharmacokinetic/pharmacodynamic indices should be functions of the anticipated densities of the infecting population.
OBJECTIVES: To determine the functional relationship between the density of bacteria and the pharmacodynamics of antibiotics, and the potential consequences of this inoculum effect on the microbiological course of antibiotic treatment of Staphylococcus aureus infections. METHODS: In vitro time-kill, MIC estimation and antibiotic bioassay experiments were performed with S. aureus ATCC 25923 to ascertain the functional relationship between rates of kill and the MICs of six classes of antibiotics and the density of bacteria exposed. The potential consequences of the observed inoculum effects on the microbiological course of antibiotic treatment are explored with a mathematical model. RESULTS: Modest or substantial inoculum effects on efficacy were observed for all six antibiotics studied, such as density-dependent declines in the rate and extent of antibiotic-mediated killing and increases in MIC. Although these measures of antibiotic efficacy declined with inoculum, this density effect did not increase monotonically. At higher densities, the rate of kill of ciprofloxacin and oxacillin declined with the antibiotic concentration. For daptomycin and vancomycin, much of this inoculum effect is due to density-dependent reductions in the effective concentration of the antibiotic. For the other four antibiotics, this density effect is primarily associated with a decrease in per-cell antibiotic concentration. With parameters in the range estimated, our mathematical model predicts that the course of antibiotic treatment can be affected by cell density; treatment protocols based on conventional (density-independent) MICs can fail to clear higher density infections. CONCLUSIONS: The MICs used for pharmacokinetic/pharmacodynamic indices should be functions of the anticipated densities of the infecting population.
Authors: C Garrigós; O Murillo; G Euba; R Verdaguer; F Tubau; C Cabellos; J Cabo; J Ariza Journal: Antimicrob Agents Chemother Date: 2010-10-04 Impact factor: 5.191
Authors: Pratik Bhagunde; Kai-Tai Chang; Renu Singh; Vandana Singh; Kevin W Garey; Michael Nikolaou; Vincent H Tam Journal: Antimicrob Agents Chemother Date: 2010-08-30 Impact factor: 5.191
Authors: Marie Vasse; Robert J Noble; Andrei R Akhmetzhanov; Clara Torres-Barceló; James Gurney; Simon Benateau; Claire Gougat-Barbera; Oliver Kaltz; Michael E Hochberg Journal: Proc Natl Acad Sci U S A Date: 2017-01-03 Impact factor: 11.205