Valsesia Giorgia, Hombach Michael, Maurer Florian P, Courvalin Patrice, Roos Malgorzata, Böttger Erik C
Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland.
Unité des Agents Antibactériens, Institut Pasteur, Paris, France.
J Clin Microbiol. 2015 Jun;53(6):1806-11. doi: 10.1128/JCM.03505-14. Epub 2015 Mar 11.
This study aimed to determine resistant-population cutoffs (RCOFFs) to allow for improved characterization of antimicrobial susceptibility patterns in bacterial populations. RCOFFs can complement epidemiological cutoff (ECOFF)-based settings of clinical breakpoints (CBPs) by systematically describing the correlation between non-wild-type and wild-type populations. We illustrate this concept by describing three paradigmatic examples of wild-type and non-wild-type Escherichia coli populations from our clinical strain database of disk diffusion diameters. The statistical determination of RCOFFs and ECOFFs and their standardized applications in antimicrobial susceptibility testing (AST) facilitates the assignment of isolates to wild-type or non-wild-type populations. This should improve the correlation of in vitro AST data and distinct antibiotic resistance mechanisms with clinical outcome facilitating the setting and validation of CBPs.
本研究旨在确定耐药人群截断值（RCOFFs），以更好地表征细菌群体中的抗菌药物敏感性模式。RCOFFs可以通过系统地描述非野生型和野生型群体之间的相关性，来补充基于流行病学截断值（ECOFF）的临床断点（CBP）设置。我们通过描述来自我们的纸片扩散法直径临床菌株数据库中的野生型和非野生型大肠杆菌群体的三个典型例子来说明这一概念。RCOFFs和ECOFFs的统计确定及其在抗菌药物敏感性测试（AST）中的标准化应用，有助于将分离株分类为野生型或非野生型群体。这应该会改善体外AST数据以及不同抗生素耐药机制与临床结果之间的相关性，从而有助于CBP的设定和验证。
