Literature DB >> 19493372

Surveillance for antimicrobial resistant organisms: potential sources and magnitude of bias.

O R Rempel1, K B Laupland.   

Abstract

Surveillance has been recognized as a fundamental component in the control of antimicrobial- resistant infections. Although surveillance data have been widely published and utilized by researchers and decision makers, little attention has been paid to assessment of their validity. We conducted this review in order to identify and explore potential types and magnitude of bias that may influence the validity or interpretation of surveillance data. Six main potential areas were assessed. These included bias related to use of inadequate or inappropriate (1) denominator data, (2) case definitions, and (3) case ascertainment; (4) sampling bias; (5) failure to deal with multiple occurrences, and (6) those related to laboratory practice and procedures. The magnitude of these biases varied considerably for the above areas within different study populations. There are a number of potential biases that should be considered in the methodological design and interpretation of antimicrobial-resistant organism surveillance.

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Year:  2009        PMID: 19493372     DOI: 10.1017/S0950268809990100

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   2.451


  24 in total

1.  Is methicillin-resistant Staphylococcus aureus replacing methicillin-susceptible S. aureus?

Authors:  Elizabeth Mostofsky; Marc Lipsitch; Gili Regev-Yochay
Journal:  J Antimicrob Chemother       Date:  2011-07-07       Impact factor: 5.790

2.  Antimicrobial resistance surveillance systems: Are potential biases taken into account?

Authors:  Olivia Rempel; Johann Dd Pitout; Kevin B Laupland
Journal:  Can J Infect Dis Med Microbiol       Date:  2011       Impact factor: 2.471

3.  Antimicrobial resistance in community-acquired Escherichia coli isolated from urinary infection: Good news or bad?

Authors:  Lindsay E Nicolle
Journal:  Can J Infect Dis Med Microbiol       Date:  2013       Impact factor: 2.471

Review 4.  Antimicrobial Resistance Surveillance in Low- and Middle-Income Countries: Progress and Challenges in Eight South Asian and Southeast Asian Countries.

Authors:  Sumanth Gandra; Gerardo Alvarez-Uria; Paul Turner; Jyoti Joshi; Direk Limmathurotsakul; H Rogier van Doorn
Journal:  Clin Microbiol Rev       Date:  2020-06-10       Impact factor: 26.132

Review 5.  Population-based epidemiology and microbiology of community-onset bloodstream infections.

Authors:  Kevin B Laupland; Deirdre L Church
Journal:  Clin Microbiol Rev       Date:  2014-10       Impact factor: 26.132

6.  Disease burden, associated mortality and economic impact of antimicrobial resistant infections in Australia.

Authors:  Teresa M Wozniak; Amalie Dyda; Greg Merlo; Lisa Hall
Journal:  Lancet Reg Health West Pac       Date:  2022-07-07

7.  Evaluation of the French surveillance system for epidemiological surveillance of antimicrobial resistance in the community and nursing homes.

Authors:  Lucie Collineau; Euriel Godebert; Sonia Thibaut; Olivier Lemenand; Gabriel Birgand; Jocelyne Caillon; Clémence Bourely
Journal:  JAC Antimicrob Resist       Date:  2022-07-04

8.  Defining the epidemiology of bloodstream infections: the 'gold standard' of population-based assessment.

Authors:  K B Laupland
Journal:  Epidemiol Infect       Date:  2012-12-06       Impact factor: 4.434

Review 9.  The Role of PK/PD Analysis in the Development and Evaluation of Antimicrobials.

Authors:  Alicia Rodríguez-Gascón; María Ángeles Solinís; Arantxa Isla
Journal:  Pharmaceutics       Date:  2021-06-03       Impact factor: 6.321

10.  Burden of community-onset bloodstream infections, Western Interior, British Columbia, Canada.

Authors:  K B Laupland; K Pasquill; E C Parfitt; P Naidu; L Steele
Journal:  Epidemiol Infect       Date:  2016-03-21       Impact factor: 4.434

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