Julia Anna Bielicki1, Rebecca Lundin, Mike Sharland. 1. From the *Paediatric Infectious Diseases Research Group, St George's University of London, London, United Kingdom; and †PENTA Foundation, Padova, Italy.
Abstract
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.
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.
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