Surveillance of Gram-negative bacteria: impact of variation in current European laboratory reporting practice on apparent multidrug resistance prevalence in paediatric bloodstream isolates

Evaluation of the Accelerate Pheno™ system for rapid identification and antimicrobial susceptibility testing of Gram-negative bacteria in bloodstream infections

Identification and antimicrobial susceptibility testing (AST) are critical steps in the management of bloodstream infections. Our objective was to evaluate the performance of the Accelerate Pheno™ System, CE v1.2 software, for identification and AST of Gram-negative pathogens from positive blood culture bottles. A total of 104 bottles positive for Gram-negative bacteria collected from inpatients throughout our institution were randomly selected after Gram staining. The time-to-identification and AST results, and the raw AST results obtained by the Accelerate Pheno™ system and routine techniques (MALDI-TOF MS and VITEK®2, EUCAST guidelines) were compared. Any discrepant AST result was tested by microdilution. The Pheno™ significantly improved turn-around times for identification (5.3 versus 23.7 h; p < 0.0001) and AST (10.7 versus 35.1 h; p < 0.0001). Complete agreement between the Accelerate Pheno™ system and the MALDI-TOF MS for identification was observed for 96.2% of samples; it was 99% (98/99) for monomicrobial samples versus 40% (3/5) for polymicrobial ones. The overall categorical agreement for AST was 93.7%; it was notably decreased for beta-lactams (cefepime 84.4%, piperacillin-tazobactam 86.5%, ceftazidime 87.6%) or Pseudomonas aeruginosa (71.9%; with cefepime 33.3%, piperacillin-tazobactam 77.8%, ceftazidime 0%). Analysis of discrepant results found impaired performance of the Accelerate Pheno™ system for beta-lactams (except cefepime) in Enterobacteriales (six very major errors) and poor performance in P. aeruginosa. The Accelerate Pheno™ system significantly improved the turn-around times for bloodstream infection diagnosis. Nonetheless, improvements in the analysis of polymicrobial samples and in AST algorithms, notably beta-lactam testing in both P. aeruginosa and Enterobacteriales, are required for implementation in routine workflow.

Temporal trends and patterns in antimicrobial-resistant Gram-negative bacteria implicated in intensive care unit-acquired infections: A cohort-based surveillance study in Istanbul, Turkey

OBJECTIVES

This study assessed trends and patterns in antimicrobial-resistant intensive care unit (ICU)-acquired infections caused by Gram-negative bacteria (GNB) in Istanbul, Turkey.

METHODS

Bacterial culture and antimicrobial susceptibility data were collected for all GNB causing nosocomial infections in five adult ICUs of a large university hospital in 2012-2015. Multiresistance patterns were categorised as multidrug-resistant (MDR), extensively drug-resistant (XDR) and pandrug-resistant (PDR). Temporal patterns and trends were assessed using regression analyses.

RESULTS

Of 991 pathogenic GNB recorded, the most frequent were Acinetobacter baumannii (35.3%), Klebsiella spp. (26.7%), Pseudomonas aeruginosa (18.1%) and Escherichia coli (6.7%). The overall infection rate decreased by 41% from 18.4 to 10.9 cases per 1000 patient-days in 2012 compared with 2015 (P<0.001), mostly representing decreases in bloodstream infections and pneumonias by A. baumannii and P. aeruginosa. The XDR proportion in A. baumannii increased from 52.4% in 2012 to 71.7% in 2015, but only one isolate was colistin-resistant. Multiresistance patterns remained stable in Klebsiella, with overall XDR and possible PDR proportions of 14.3% and 1.9%, respectively. A back-to-susceptibility trend was noted for P. aeruginosa in which the non-MDR proportion increased from 53.3% in 2012 to 70.6% in 2015. Moreover, 87.9% of E. coli and 39.5% of Enterobacter isolates were MDR, but none was XDR.

CONCLUSIONS

Antimicrobial resistance patterns in pathogenic GNB continuously change over time and may not reflect single-agent resistance trends. The proportionate amount of antimicrobial-resistant GNB may persist despite overall decreasing infection rates. Timely regional surveillance data are thus imperative for optimal infection control.