A Retrospective Cohort Analysis Shows that Coadministration of Minocycline with Colistin in Critically Ill Patients Is Associated with Reduced Frequency of Acute Renal Failure.

Nonclinical studies have suggested that oxidative damage, caspase-mediated apoptosis, and inducible nitric oxide synthase levels may be involved in the pathogenesis of colistin (CST)-associated acute renal failure. MIN inhibits caspase 1, caspase 3, and inducible nitric oxide synthase, leading to the hypothesis that coadministration of CST with MIN (CST-MIN) may reduce the incidence of acute renal failure as well as produce additive or synergistic antimicrobial effects. A multicenter retrospective cohort study was conducted using the Premier Research database to examine the impact of CST-MIN on acute renal failure. Inclusion criteria were as follows: age of ≥18 years, intensive care unit admission at CST initiation, primary International Classification of Diseases 9 (ICD-9) diagnosis of pneumonia or sepsis, nondialysis at hospital admission, and discharge between January 2010 and December 2015. ICD-9 code 584.XX or ICD-10 code N17 was used to define acute renal failure. Baseline comparisons, 1:8 propensity score matching, and confirmatory logistic regression analyses were conducted. In total, 4,817 patients received CST and met inclusion criteria; 93 received CST-MIN. Unadjusted frequency of acute renal failure was significantly lower in patients receiving CST-MIN than CST (11.8% versus 23.7%, P = 0.007). Similar results were seen in propensity score matching (12.0% versus 22.3%, P = 0.031) and logistic regression analyses (odds ratio of 0.403, P = 0.006). Mortalities and 30-day readmission rates were similar between groups. The acute renal failure rate was not impacted by prevalence of baseline renal disease. CST-MIN in critically ill patients may reduce CST-associated acute renal failure. Further evaluation of this combination in prospective clinical studies is warranted.

Use of Monte Carlo simulation and considerations for PK-PD targets to support antibacterial dose selection.

Monte Carlo simulation is used to generate data for pharmacokinetic-pharmacodynamic (PK-PD) target attainment analyses to assess antibacterial dosing regimens in early and late stage drug development. Careful consideration of the quality of data for pharmacokinetics, non-clinical PK-PD targets for efficacy, the choice of the bacterial reduction endpoint upon which the PK-PD target is based, variability in the PK-PD target, and effect site exposures ensures optimal dose selection. Relationships between drug exposure and efficacy and/or safety endpoints based on clinical data can also be applied to simulated data to support dose selection. These in silico analyses, conducted throughout drug development, provide the greatest opportunity to de-risk the development of antibacterial agents.

Reevaluation of Enterobacteriaceae MIC/disk diffusion zone diameter regression scattergrams for 9 beta-lactams: adjustments of breakpoints for strains producing extended spectrum beta-lactamases.

Validity of the current susceptibility breakpoint criteria for 9 beta-lactam antimicrobials and performance of proposed alternative breakpoints to improve prediction of clinical outcomes were analyzed by testing a contemporary collection of 350 Enterobacteriaceae, enriched for an overrepresentative collection of 70 (20.0%) strains producing extended-spectrum beta-lactamases (ESBLs). The majority of the strains were isolated from bloodstream infections (83.7% of the entire collection and 85.7% of the ESBL subset). The 9 beta-lactam antimicrobials analyzed were aztreonam, cefepime, cefotaxime, cefotetan, cefoxitin, ceftazidime, ceftriaxone, ceftizoxime, and cefuroxime. Reference broth microdilution MIC results were compared with those zone diameters obtained by the standardized disk diffusion test. The correlation coefficient (r) was acceptable for all antimicrobials, ranging from 0.87 (cefotetan) to 0.97 (aztreonam, cefotaxime, and ceftazidime). Using the current susceptible breakpoint criteria for Enterobacteriaceae, the intermethod categorical agreement ranged from 90.6% (cefotaxime) to 98.0% (ceftazidime). Very major (false-susceptible by disk test) and major errors (false-resistant) were nil (0.0%) for 6 of the 9 beta-lactams. Minor error rates ranged from only 0.9% (cefotetan) to 9.4% (cefotaxime). The proposed MIC breakpoint criteria (generally lower) adjusted to levels to accurately detect ESBL-producing strains and better predict clinical outcomes, also had acceptable intermethod concordance ranging from 90.6% (cefotetan) to 100.0% (ceftazidime). Remarkably, an improvement in the intermethod categorical agreement ranging from +1.7% to +8.3% was observed for 7 of the 9 antimicrobials, including the ESBL index or screening compounds (aztreonam, ceftazidime, cefotaxime, and ceftriaxone). No change in the breakpoint criteria, with removal of the intermediate category was tentatively proposed for cefoxitin and cefuroxime, resulting in an increase of the serious intermethod errors (very major and major), but the absolute intermethod agreement remained highly acceptable at 90.6% to 93.4%. Although the current breakpoint criteria remain acceptable in minimizing intermethod discords, the alternative susceptible breakpoint criteria proposed by combining pharmacokinetic/pharmacodynamic (PK/PD), microbiology MIC population analyses, and clinical success parameters possess improved intermethod agreement for the ESBL screening drugs and 5 other broad-spectrum beta-lactam compounds. The Clinical Laboratory Standards Institute (formerly, the National Committee for Clinical Laboratory Standards) should consider these changes to facilitate the detection of all Enterobacteriaceae with low PK/PD target attainment rates, therefore having the potential for suboptimal responses with usual therapeutic dosing.

Application of a mathematical model to prevent in vivo amplification of antibiotic-resistant bacterial populations during therapy.

The worldwide increase in the prevalence of multi-antibiotic-resistant bacteria has threatened the physician's ability to provide appropriate therapy for infections. The relationship between antimicrobial drug concentration and infecting pathogen population reduction is of primary interest. Using data derived from mice infected with the bacterium Pseudomonas aeruginosa and treated with a fluoroquinolone antibiotic, a mathematical model was developed that described relationships between antimicrobial drug exposures and changes in drug-susceptible and -resistant bacterial subpopulations at an infection site. Dosing regimens and consequent drug exposures that amplify or suppress the emergence of resistant bacterial subpopulations were identified and prospectively validated. Resistant clones selected in vivo by suboptimal regimens were characterized. No mutations were identified in the quinolone resistance-determining regions of gyrA/B or parC/E. However, all resistant clones demonstrated efflux pump overexpression. At base line, MexAB-OprM, MexCD-OprJ, and MexEF-OprN were represented in the drug-resistant population. After 28 hours of therapy, MexCD-OprJ became the predominant pump expressed in the resistant clones. The likelihood of achieving resistance-suppression exposure in humans with a clinically prescribed antibiotic dose was determined. The methods developed in this study provide insight regarding how mathematical models can be used to identify rational dosing regimens that suppress the amplification of the resistant mutant population.