Journal article
F. van Leth, Casper den Heijer, M. Beerepoot, E. Stobberingh, S. Geerlings, C. Schultsz
Future Microbiology, 2017
Future Microbiology, 2017
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APA
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van Leth, F., den Heijer, C., Beerepoot, M., Stobberingh, E., Geerlings, S., & Schultsz, C. (2017). Rapid assessment of antimicrobial resistance prevalence using a Lot Quality Assurance sampling approach. Future Microbiology.
Chicago/Turabian
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Leth, F. van, Casper den Heijer, M. Beerepoot, E. Stobberingh, S. Geerlings, and C. Schultsz. “Rapid Assessment of Antimicrobial Resistance Prevalence Using a Lot Quality Assurance Sampling Approach.” Future Microbiology (2017).
MLA
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van Leth, F., et al. “Rapid Assessment of Antimicrobial Resistance Prevalence Using a Lot Quality Assurance Sampling Approach.” Future Microbiology, 2017.
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@article{f2017a,
title = {Rapid assessment of antimicrobial resistance prevalence using a Lot Quality Assurance sampling approach.},
year = {2017},
journal = {Future Microbiology},
author = {van Leth, F. and den Heijer, Casper and Beerepoot, M. and Stobberingh, E. and Geerlings, S. and Schultsz, C.}
}
Abstract
AIM Increasing antimicrobial resistance (AMR) requires rapid surveillance tools, such as Lot Quality Assurance Sampling (LQAS).
MATERIALS & METHODS LQAS classifies AMR as high or low based on set parameters. We compared classifications with the underlying true AMR prevalence using data on 1335 Escherichia coli isolates from surveys of community-acquired urinary tract infection in women, by assessing operating curves, sensitivity and specificity.
RESULTS Sensitivity and specificity of any set of LQAS parameters was above 99% and between 79 and 90%, respectively. Operating curves showed high concordance of the LQAS classification with true AMR prevalence estimates.
CONCLUSION LQAS-based AMR surveillance is a feasible approach that provides timely and locally relevant estimates, and the necessary information to formulate and evaluate guidelines for empirical treatment.