RT Journal Article
SR Electronic
T1 Urinary tract pathogens and resistance pattern
JF Journal of Clinical Pathology
JO J Clin Pathol
FD BMJ Publishing Group Ltd and Association of Clinical Pathologists
SP jcp.2009.074617
DO 10.1136/jcp.2009.074617
A1 R Chakupurakal
A1 M Ahmed
A1 D N Sobithadevi
A1 S Chinnappan
A1 T Reynolds
YR 2010
UL http://jcp.bmj.com/content/early/2010/05/23/jcp.2009.074617.abstract
AB Background Epidemiology and resistance patterns of bacterial pathogens in paediatric urinary tract infections (UTIs) show large inter-regional variability, and rates of bacterial resistance are changing due to different antibiotic treatment. Empiric therapy to treat UTI should be tailored to the surveillance data on the epidemiology and resistance patterns of common uropathogens to reduce treatment failures and emergence of bacterial resistance within the community.Objective A retrospective data review was carried out to evaluate the resistance patterns to commonly used antibiotics in children with culture proven UTIs.Methods All infants and children with culture proven UTI from 2002 to 2008 were included. Urine culture was deemed positive with a pure growth >105 (single organism).Results A total of 547 UTIs were confirmed on urine cultures in 337 patients. An average of 78 cases were diagnosed each year. E coli was the most commonly grown pathogen (92%). From 2002 to 2008, rising resistance patterns were noted for trimethoprim (p≤0.05) and Augmentin (p≤0.001). In contrast, resistance to cefalexin and nitrofurantoin remained relatively low (11% and 7%, respectively, in 2008).Conclusion Our data suggest that there has been an increasing resistance trend to the first-line antibiotics like trimethoprim and Augmentin against E coli. In accordance with NICE (National Institute for Health and Clinical Excellence) guidance, each region should monitor resistance patterns to urinary pathogens on a regular basis and use antibiotics with a low resistance pattern. Further studies are required from other centres in the UK to look at similar data.