Contemporary analysis of ETEST for antibiotic susceptibility and minimum inhibitory concentration agreement against Pseudomonas aeruginosa from patients with cystic fibrosis

Abstract

Objectives Cystic fibrosis (CF) acute pulmonary exacerbations are often caused by Pseudomonas aeruginosa, including multi-drug resistant strains. Optimal antibiotic therapy is required to return lung function and should be guided by in vitro susceptibility results. There are sparse data describing ETEST performance for CF isolates using contemporary isolates, methods and interpretation, as well as novel antibiotics, such as ceftazidime–avibactam and ceftolozane–tazobactam. Methods Pseudomonas aeruginosa (n = 105) isolated during pulmonary exacerbation from patients with CF were acquired from 3 US hospitals. Minimum inhibitory concentrations (MICs) were assessed by reference broth microdilution (BMD) and ETEST for aztreonam, cefepime, ceftazidime, ceftazidime–avibactam, ceftolozane–tazobactam, ciprofloxacin, levofloxacin, meropenem, piperacillin–tazobactam, and tobramycin. Broth microdilution was conducted in concordance with the Clinical and Laboratory Standards Institute M100. ETEST methodology reflected package insert recommendations. Performance of ETEST strips was evaluated using the Food and Drug Administration (FDA) and Susceptibility Testing Manufacturers Association (STMA) guidance. Results Of the 105 P. aeruginosa included, 46% had a mucoid phenotype. ETEST MICs typically read 0–1 dilution higher than BMD for all drugs. Categorical agreement and essential agreement ranged from 64 to 93% and 63 to 86%, respectively. The majority of observed errors were minor. A single very major error occurred with ceftazidime (4.2%). For ceftazidime–vibactam, 2 very major errors were observed and both were within essential agreement. Major errors occurred for aztreonam (3.3%), cefepime (9.4%), ceftazidime–avibactam (5.3%, adjusted 2.1%), ceftolozane–tazobactam (1%), meropenem (3.3%), piperacillin–tazobactam (2.9%), and tobramycin (1.5%). Conclusions ETEST methods performed conservatively for most antibiotics against this challenging collection of P. aeruginosa from patients with CF.

Multicenter, Prospective Validation of a Phenotypic Algorithm to Guide Carbapenemase Testing in Carbapenem-ResistantPseudomonas aeruginosaUsing the ERACE-PA Global Surveillance Program

“…Indeed, the algorithm false negatives were assessed by reference broth microdilution, revealing that 83% were confirmed to be algorithm-negative (ie, susceptible to either cefepime or ceftazidime). This is not unexpected; particularly when isolates’ MICs are at or around the susceptibility breakpoint, there is a high potential for categorical disagreement as the acceptable variability of MIC testing can vary by 100% on either side of the MIC result [ 17 ]. In the analysis of the algorithm, we utilized the MIC result from the submitting sites as it represents (1) a worst-case assessment of the proposed algorithm and (2) is clinically applicable as it reflects the methods utilized regularly in clinical practice.…”

Exploiting lung adaptation and phage steering to clear pan-resistant Pseudomonas aeruginosa infections in vivo

“…Each isolate harvested from mice sacrificed 48 h post- bacterial infection was grown on Mueller–Hinton broth overnight at 37 °C, 180 RPM and then disk diffusion assay was performed 23 . Breakpoints were established according to the latest EUCAST guidelines 23 .The minimum inhibitory concentration (MIC) of antibiotics meropenem (32 ug/ml) and tobramycin (257 ug/ml) was determined via E-test strips provided by bioMérieux 40 . Overnight cultures of each isolate we adjusted to a McFarland standard of 0.5 and each inoculum was applied to a Mueller–Hinton Agar plate with a sterile cotton swab and allowed to dry for 10 min.…”

Antibiotic Resistance Detection in Pseudomonas aeruginosa: Recent Strategies, Advances, and Challenges

“…Besides the advantages of the use AST automated systems, most clinical laboratories employ agar-based AST methods to test CF isolates, since automated systems have historically performed poorly for such samples. [46][47][48] When automated AST is performed, major errors in MIC prediction are observed in the case of slow-growing bacteria. The errors can be identified by comparing the MICs obtained by testing using automated technology such as Vitek 2 ® and the results obtained from the traditional culture-based susceptibility testing assays such as Etest or broth microdilution.…”