MacKinnon Melissa C, Pearl David L, Carson Carolee A, Parmley E Jane, McEwen Scott A
Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Rd E, Guelph, Ontario, N1G 2W1, Canada.
Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Rd E, Guelph, Ontario, N1G 2W1, Canada.
Prev Vet Med. 2018 Jun 1;154:9-17. doi: 10.1016/j.prevetmed.2018.03.010. Epub 2018 Mar 16.
Antimicrobial resistance (AMR) and related multidrug resistance (MDR) are important global public health issues. The Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) conducts surveillance of AMR in enteric bacteria and monitors MDR. However, the analysis of MDR is complicated by the lack of consensus for MDR definitions. The objectives were to describe the most common resistance patterns in generic E. coli isolates from chicken cecal samples and determine the impact of using different MDR metrics for analysis of annual and regional variation in MDR. From 2006 to 2015, 1598 E. coli isolates were collected from chickens at slaughter for CIPARS. Three MDR classification metrics were used: MDR-drug (MDR if the isolate was resistant (R) to ≥3 of the 13 antimicrobials); MDR-cat (MDR if R to ≥3 of the 9 antimicrobials categories); and MDR-class (MDR if R to ≥3 of the 6 antimicrobial classes). The most frequent resistance patterns overall, and by year and region were extracted along with patterns that included resistance to quinolones, and third generation cephalosporins and/or β-lactams with β-lactamase inhibitors. For each MDR metric, mixed logistic regression models, which included random intercepts for abattoir, were fitted to analyze the association between prevalence of MDR, and year and region. Interaction effects between year and region were evaluated. Overall, and in all years and regions, non-resistant was the most common resistance pattern (24.9%, 95% CI 22.8-27.1%). Resistance patterns that included third generation cephalosporins and β-lactams with β-lactamase inhibitors were common. The prevalence of MDR was variable: MDR-class 38.5% (95% CI 36.1-41.0%); MDR-cat 49.4% (95% CI 46.9-51.9%); and MDR-drug 53.3% (95% CI 50.8-55.8%). Based on models fitted with individual fixed effects, significant annual variation in the prevalence of MDR was identified with MDR-drug and MDR-class models. Significant regional variation was identified for all three MDR metric models. Significant interaction effects between year and region were identified with the MDR-drug and MDR-cat multivariable mixed logistic regression models. The interpretation of the association between the prevalence of MDR, and year and region differed depending on the MDR metric used. These results are supportive of the previous concerns that caution must be taken when comparing MDR results between studies. Global consensus is needed for the optimal MDR classification metric for foodborne enteric bacteria AMR surveillance.
抗菌药物耐药性（AMR）及相关的多重耐药性（MDR）是重要的全球公共卫生问题。加拿大抗菌药物耐药性监测综合项目（CIPARS）对肠道细菌中的AMR进行监测，并对MDR进行监控。然而，由于缺乏对MDR定义的共识，MDR的分析变得复杂。目的是描述来自鸡盲肠样本的普通大肠杆菌分离株中最常见的耐药模式，并确定使用不同的MDR指标分析MDR年度和区域变化的影响。2006年至2015年期间，为CIPARS从屠宰鸡中收集了1598株大肠杆菌分离株。使用了三种MDR分类指标：MDR-药物（如果分离株对13种抗菌药物中的≥3种耐药（R），则为MDR）；MDR-类别（如果对9种抗菌药物类别中的≥3种耐药，则为MDR）；以及MDR-分类（如果对6种抗菌药物类别中的≥3种耐药，则为MDR）。提取了总体上以及按年份和地区划分的最常见耐药模式，以及包括对喹诺酮类、第三代头孢菌素和/或带有β-内酰胺酶抑制剂的β-内酰胺类耐药的模式。对于每个MDR指标，拟合了包含屠宰场随机截距的混合逻辑回归模型，以分析MDR患病率与年份和地区之间的关联。评估了年份和地区之间的交互作用。总体而言，在所有年份和地区，非耐药是最常见的耐药模式（24.9%，95%置信区间22.8 - 27.1%）。包括第三代头孢菌素和带有β-内酰胺酶抑制剂的β-内酰胺类的耐药模式很常见。MDR的患病率各不相同：MDR-分类为38.5%（95%置信区间36.1 - 41.0%）；MDR-类别为49.4%（95%置信区间46.9 - 51.9%）；MDR-药物为53.3%（95%置信区间50.8 - 55.8%）。基于拟合了个体固定效应的模型，在MDR-药物和MDR-分类模型中确定了MDR患病率的显著年度变化。在所有三种MDR指标模型中都确定了显著的区域差异。在MDR-药物和MDR-类别多变量混合逻辑回归模型中确定了年份和地区之间的显著交互作用。根据所使用的MDR指标，MDR患病率与年份和地区之间关联的解释有所不同。这些结果支持了之前的担忧，即在比较不同研究的MDR结果时必须谨慎。对于食源肠道细菌AMR监测的最佳MDR分类指标，需要全球达成共识。
