van Leth Frank, den Heijer Casper, Beerepoot Mariëlle, Stobberingh Ellen, Geerlings Suzanne, Schultsz Constance
Department of Global Health, Academic Medical Center, University of Amsterdam, Amsterdam Institute for Global Health & Development, Amsterdam, The Netherlands.
Department of Medical Microbiology, Maastricht University, School of Public Health & Primary Care, Maastricht, The Netherlands.
Future Microbiol. 2017 Apr;12:369-377. doi: 10.2217/fmb-2016-0170. Epub 2017 Mar 24.
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.
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.
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.
日益增加的抗菌药物耐药性（AMR）需要快速监测工具，如批质量保证抽样法（LQAS）。
LQAS根据设定参数将AMR分为高或低。我们通过评估操作曲线、敏感性和特异性，利用1335株来自女性社区获得性尿路感染调查的大肠杆菌分离株数据，将分类结果与实际的AMR流行率进行比较。
任何一组LQAS参数的敏感性和特异性分别高于99%和介于79%至90%之间。操作曲线显示LQAS分类与实际AMR流行率估计高度一致。
基于LQAS的AMR监测是一种可行的方法，可提供及时且与当地相关的估计，以及制定和评估经验性治疗指南所需的信息。
