Van Eldere Johan, Mera Robertino M, Miller Linda A, Poupard James A, Amrine-Madsen Heather
University Hospital Gasthuisberg, Leuven, Belgium.
Antimicrob Agents Chemother. 2007 Oct;51(10):3491-7. doi: 10.1128/AAC.01581-06. Epub 2007 Aug 6.
We investigated the impact of the usage of antibiotics in ambulatory patients in Belgium in 147 defined geographical circumscriptions and at the individual isolate level. The study included 14,448 Streptococcus pneumoniae strains collected by the Belgium national reference lab from 1994 to 2004. Additional risk factors for resistance, such as population density/structure and day care attendance, were investigated for the same time-space window. A statistical model that included resistance to two or more antimicrobial classes offered the best fit for measuring the changes in nonsusceptibility to penicillin, macrolides, and tetracycline over time and place in Belgium. Analysis at the geographic level identified antimicrobial consumption with a 1-year lag (0.5% increase per additional defined daily dose) and population density as independent predictors of multiple resistance. Independent risk factors at the isolate level were age (odds ratio [OR], 1.55 for children aged <5 years), population density (7% increase in multiple resistance per 100 inhabitants/km(2)), conjugate 7-valent vaccine serotype (OR, 14.3), location (OR, 1.55 for regions bordering high-resistance France), and isolate source (OR, 1.54 for ear isolates). The expansion of multiple-resistant strains explains most of the overall twofold increase and subsequent decrease in single antimicrobial resistance between 1994 and 2004. We conclude that factors in addition to antibiotic use, such as high population density and proximity to high-resistance regions, favor multiple resistance. Regional resistance rates are not linearly related to actual antibiotic use but are linked to past antibiotic use plus a combination of demographic and geographic factors.
我们在比利时147个明确界定的地理区域内,针对门诊患者使用抗生素的情况以及单个分离株层面展开了调查。该研究纳入了比利时国家参考实验室在1994年至2004年期间收集的14448株肺炎链球菌菌株。同时,在相同的时空范围内,我们还研究了其他耐药风险因素,如人口密度/结构以及日托机构的出勤率。一个包含对两种或更多抗菌药物类别耐药情况的统计模型,最适合用于衡量比利时青霉素、大环内酯类和四环素的非敏感性随时间和地点的变化。地理层面的分析确定,抗菌药物消耗量滞后1年(每增加一个限定日剂量,耐药率增加0.5%)以及人口密度是多重耐药的独立预测因素。分离株层面的独立风险因素包括年龄(<5岁儿童的优势比[OR]为1.55)、人口密度(每100名居民/平方公里多重耐药率增加7%)、7价结合疫苗血清型(OR为14.3)、地点(与高耐药率的法国接壤地区的OR为1.55)以及分离株来源(耳部分离株的OR为1.54)。多重耐药菌株的增加解释了1994年至2004年间单一抗菌药物耐药总体上两倍增长及随后下降的大部分原因。我们得出结论,除抗生素使用外,诸如高人口密度和靠近高耐药地区等因素也有利于多重耐药的发生。区域耐药率与实际抗生素使用并非线性相关,而是与过去的抗生素使用以及人口和地理因素的综合作用有关。