An in vitro method of detecting synergy which is simple to perform, accurate, and reproducible and has the potential for clinical extrapolation is desirable. Time-kill and checkerboard methods are the most widely used techniques to assess synergy but are time-consuming and labor-intensive. The Epsilometer test (E test), a less technically demanding test, has not been well studied for synergy testing. We performed synergy testing of Escherichia coli ATCC 35218, Enterobacter cloacae ATCC 23355, Pseudomonas aeruginosa ATCC 27853, and Staphylococcus aureus ATCC 29213 with various combinations of cefepime or ceftazidime with tobramycin or ciprofloxacin using time-kill, checkerboard, and E test techniques. Time-kill testing was performed against each organism alone and in combinations at one-fourth times the MIC (1/4 x MIC) and 2 x MIC. With checkerboard tests, the same combinations were studied at concentrations ranging from 1/32 x to 4 x MIC. Standard definitions for synergy, indifference, and antagonism were utilized. E test strips were crossed at a 90 degree angle so the scales met at the MIC of each drug alone, and the fractional inhibitory concentrations index was calculated on the basis of the resultant zone on inhibition. All antimicrobial combinations demonstrated some degree of synergy against the test organisms, and antagonism was infrequent. Agreement with time-kill testing ranged from 44 to 88% and 63 to 75% by the checkerboard and E test synergy methods, respectively. Despite each of these methods utilizing different conditions and endpoints, there was frequent agreement among the methods. Further comparisons of the E test synergy technique with the checkerboard and time-kill methods are warranted.

A panel of experts was convened by the Infectious Diseases Society of America (IDSA) to update the 2004 clinical practice guideline on outpatient parenteral antimicrobial therapy (OPAT) [1]. This guideline is intended to provide insight for healthcare professionals who prescribe and oversee the provision of OPAT. It considers various patient features, infusion catheter issues, monitoring questions, and antimicrobial stewardship concerns. It does not offer recommendations on the treatment of specific infections. The reader is referred to disease- or organism-specific guidelines for such support.

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Determination of the attributable hospital cost and length of stay (LOS) are of critical importance for patients, providers, and payers who must make rational and informed decisions about patient care and the allocation of resources. The objective of the present study was to determine the additional total hospital cost and LOS attributable to health care-associated infections (HAIs) caused by antibiotic-resistant, gram-negative (GN) pathogens. A single-center, retrospective, observational comparative cohort study was performed. The study involved 662 patients admitted from 2000 to 2008 who developed HAIs caused by one of following pathogens: Acinetobacter spp., Enterobacter spp., Escherichia coli, Klebsiella spp., or Pseudomonas spp. The attributable total hospital cost and LOS for HAIs caused by antibiotic-resistant GN pathogens were determined by comparison with the hospital costs and LOS for a control group with HAIs due to antibioticsusceptible GN pathogens. Statistical analyses were conducted by using univariate and multivariate analyses. Twenty-nine percent of the HAIs were caused by resistant GN pathogens, and almost 16% involved a multidrugresistant GN pathogen. The additional total hospital cost and LOS attributable to antibiotic-resistant HAIs caused by GN pathogens were 29.3% (P < 0.0001; 95% confidence interval, 16.23 to 42.35) and 23.8% (P ‫؍‬ 0.0003; 95% confidence interval, 11.01 to 36.56) higher than those attributable to HAIs caused by antibioticsusceptible GN pathogens, respectively. Significant covariates in the multivariate analysis were age >12 years, pneumonia, intensive care unit stay, and neutropenia. HAIs caused by antibiotic-resistant GN pathogens were associated with significantly higher total hospital costs and increased LOSs compared to those caused by their susceptible counterparts. This information should be used to assess the potential cost-efficacy of interventions aimed at the prevention of such infections.