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OBJECTIVES: The objective of this study was to evaluate the ability of weighted-incidence syndromic combination antibiograms (WISCAs) to inform the selection of empirical antibiotic regimens for suspected paediatric bloodstream infections (BSIs) by comparing WISCAs derived using data from single hospitals and from a multicentre surveillance dataset. METHODS: WISCAs were developed by estimating the coverage of five empirical antibiotic regimens for childhood BSI using a Bayesian decision tree. The study used microbiological data on ∼2000 bloodstream isolates collected over 2 years from 19 European hospitals. We evaluated the ability of a WISCA to show differences in regimen coverage at two exemplar hospitals. For each, a WISCA was first calculated using only their local data; a second WISCA was calculated using pooled data from all 19 hospitals. RESULTS: The estimated coverage of the five regimens was 72%-86% for Hospital 1 and 79%-94% for Hospital 2, based on their own data. In both cases, the best regimens could not be definitively identified because the differences in coverage were not statistically significant. For Hospital 1, coverage estimates derived using pooled data gave sufficient precision to reveal clinically important differences among regimens, including high coverage provided by a narrow-spectrum antibiotic combination. For Hospital 2, the hospital and pooled data showed signs of heterogeneity and the use of pooled data was judged not to be appropriate. CONCLUSIONS: The Bayesian WISCA provides a useful approach to pooling information from different sources to guide empirical therapy and could increase confidence in the selection of narrow-spectrum regimens.

Objectives: The objective of this study was to evaluate the ability of weighted-incidence syndromic combination antibiograms (WISCAs) to inform the selection of empirical antibiotic regimens for suspected paediatric bloodstream infections (BSIs) by comparing WISCAs derived using data from single hospitals and from a multicentre surveillance dataset. Methods: WISCAs were developed by estimating the coverage of five empirical antibiotic regimens for childhood BSI using a Bayesian decision tree. The study used microbiological data on ~2000 bloodstream isolates collected over 2 years from 19 European hospitals. We evaluated the ability of a WISCA to show differences in regimen coverage at two exemplar hospitals. For each, a WISCA was first calculated using only their local data; a second WISCA was calculated using pooled data from all 19 hospitals. Results: The estimated coverage of the five regimens was 72%-86% for Hospital 1 and 79%-94% for Hospital 2, based on their own data. In both cases, the best regimens could not be definitively identified because the differences in coverage were not statistically significant. For Hospital 1, coverage estimates derived using pooled data gave sufficient precision to reveal clinically important differences among regimens, including high coverage provided by a narrow-spectrum antibiotic combination. For Hospital 2, the hospital and pooled data showed signs of heterogeneity and the use of pooled data was judged not to be appropriate. Conclusions: The Bayesian WISCA provides a useful approach to pooling information from different sources to guide empirical therapy and could increase confidence in the selection of narrow-spectrum regimens. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.

Item does not contain fulltext BACKGROUND: Surveillance of antimicrobial resistance (AMR) is central for defining appropriate strategies to deal with changing AMR levels. It is unclear whether childhood AMR patterns differ from those detected in isolates from adult patients. METHODS: Resistance percentages of nonduplicate Staphylococcus aureus, Streptococcus pneumoniae, Enterococcus faecalis, Enterococcus faecium, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa bloodstream isolates from children less than 18 years of age reported to the Antibiotic Resistance and Prescribing in European Children (ARPEC) project were compared with all-age resistance percentages reported by the European Antimicrobial Resistance Surveillance Network (EARS-Net) for the same pathogen-antibiotic class combinations, period and countries. In addition, resistance percentages were compared between ARPEC isolates from children less than 1 year of age and children greater than or equal to1 year of age. RESULTS: Resistance percentages for many important pathogen-antibiotic class combinations were different for ARPEC isolates compared with EARS-Net. E. coli and K. pneumoniae fluoroquinolone resistance percentages were substantially lower in ARPEC (13.4% and 17.9%) than in EARS-Net (23.0% and 30.7%), whereas the reverse was true for all pathogen-antibiotic class combinations in P. aeruginosa (for example, 27.3% aminoglycoside resistance in ARPEC, 19.3% in EARS-Net, 32.8% carbapenem resistance in ARPEC and 20.5% in EARS-Net), and for S. pneumoniae and macrolide resistance. For many Gram-negative pathogen-antibiotic class combinations, isolates from children greater than or equal to 1 year of age showed higher resistance percentages than isolates from children less than 1 year of age. CONCLUSIONS: Age-stratified presentation of resistance percentage estimates by surveillance programs will allow identification of important variations in resistance patterns between different patient groups for targeted intervention. 01 juli 2015

chap. 17; International audience

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International audience