Literature DB >> 17642708

Application of WHONET for the surveillance of antimicrobial resistance.

A Sharma1, P S Grover.   

Abstract

World over antimicrobial resistance is a major public health problem. The WHONET software program puts each laboratory data into a common code and file format, which can be merged for national or global collaboration of antimicrobial resistance surveillance. In this study, antimicrobial sensitivity of 4,289 bacterial isolates was studied by Kirby-Bauer disk diffusion method. -lactamase production was assessed by iodometric test method. Extended spectrum -lactamase (ESBLs) were screened by ceftazidime disk sensitivity. Drug resistance was high in most of the isolates. It was maximum (80-94%) for ampicillin, nalidixic acid and cotrimoxazole. It varied between 40-60% for gentamicin, clindamycin, fluoroquinolones and coamoxyclav. It ranged from 21 to 38% for amikacin and third generation cephalosporins. Constitutive -lactamase production was highest in S.aureus (28.9%) and ESBL production was maximum in Klebsiella spp. (53.6%). WHONET software has in-built analysis program which helps in forming hospital drug policy, identification of hospital outbreaks and recognition of quality control problems in the laboratory.

Entities:  

Year:  2004        PMID: 17642708

Source DB:  PubMed          Journal:  Indian J Med Microbiol        ISSN: 0255-0857            Impact factor:   0.985


  3 in total

Review 1.  Integrated Multilevel Surveillance of the World's Infecting Microbes and Their Resistance to Antimicrobial Agents.

Authors:  Thomas F O'Brien; John Stelling
Journal:  Clin Microbiol Rev       Date:  2011-04       Impact factor: 26.132

2.  Application of WHONET in the Antimicrobial Resistance Surveillance of Uropathogens: A First User Experience from Nepal.

Authors:  A N Ghosh; D R Bhatta; M T Ansari; H K Tiwari; J P Mathuria; A Gaur; H S Supram; S Gokhale
Journal:  J Clin Diagn Res       Date:  2013-05-01

3.  Biochemical phenotypes to discriminate microbial subpopulations and improve outbreak detection.

Authors:  Alicia Galar; Martin Kulldorff; Wallis Rudnick; Thomas F O'Brien; John Stelling
Journal:  PLoS One       Date:  2013-12-31       Impact factor: 3.240

  3 in total

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