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2003-2010 年比利时侵袭性肺炎球菌病中对苯唑西林的抗菌药物耐药性:改变临床断点的影响。

Antimicrobial resistance to benzylpenicillin in invasive pneumococcal disease in Belgium, 2003-2010: the effect of altering clinical breakpoints.

机构信息

Scientific Institute of Public Health, Healthcare Associated Infections & Antimicrobial Resistance, Brussels, Belgium.

Belgian National Reference Laboratory for Pneumococci, University Hospital, Leuven, Belgium.

出版信息

Epidemiol Infect. 2013 Mar;141(3):490-5. doi: 10.1017/S0950268812001057. Epub 2012 Jun 7.

DOI:10.1017/S0950268812001057
PMID:22677465
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3566593/
Abstract

The Belgian data (2003-2010) for the European Antimicrobial Resistance Surveillance Network (EARS-Net) showed a significant decreasing trend in the proportion of penicillin non-susceptible Streptococcus pneumoniae (9·4% to <1%) from blood and CSF isolates. We found that 75% of this decrease was explained by a change in Clinical and Laboratory Standards Institute (CLSI) breakpoints as the trend disappeared if only the new breakpoints were applied. Applying only European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints also resulted in a relatively stable proportion of penicillin non-susceptibility (average 5%), but this proportion was 7-13 times higher than with the new CLSI breakpoints. When the new CLSI breakpoints alone are used, fewer than 1% of bacteraemia isolates were penicillin non-susceptible during the entire period, but the proportion of non-susceptible meningitis isolates rose from 6·3% in 2003 to 15·9% between 2003 and 2010. Changing breakpoints should lead to retrospective analysis of historical data to minimize wrongly interpreting resistance trends.

摘要

比利时 2003-2010 年欧洲抗菌药物耐药性监测网络(EARS-Net)的数据显示,血和脑脊液分离株中青霉素不敏感肺炎链球菌的比例呈显著下降趋势(9.4%降至<1%)。我们发现,75%的下降可以用临床和实验室标准协会(CLSI)折点的变化来解释,如果只应用新折点,该趋势就会消失。仅应用欧洲抗菌药物敏感性试验委员会(EUCAST)折点也会导致青霉素不敏感的比例相对稳定(平均 5%),但这一比例比新 CLSI 折点高 7-13 倍。如果只应用新 CLSI 折点,整个时期血培养分离株的青霉素不敏感率不到 1%,但脑膜炎分离株的不敏感率从 2003 年的 6.3%上升到 2003-2010 年的 15.9%。改变折点应导致对历史数据进行回顾性分析,以尽量减少对耐药趋势的错误解释。

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