Hartnack Sonja, Odoch Terence, Kratzer Gilles, Furrer Reinhard, Wasteson Yngvild, L'Abée-Lund Trine M, Skjerve Eystein
Section of Epidemiology, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 270, 8057, Zurich, Switzerland.
Department of Biosecurity, Ecosystems and Veterinary Public Health, College of Veterinary Medicine, Animal Resources and Biosecurity (COVAB), Makerere University, P.O. Box 7062, Kampala, Uganda.
BMC Vet Res. 2019 Jun 24;15(1):212. doi: 10.1186/s12917-019-1965-y.
Multi-drug resistant bacteria are seen increasingly and there are gaps in our understanding of the complexity of antimicrobial resistance, partially due to a lack of appropriate statistical tools. This hampers efficient treatment, precludes determining appropriate intervention points and renders prevention very difficult.
We re-analysed data from a previous study using additive Bayesian networks. The data contained information on resistances against seven antimicrobials and seven potential risk factors from 86 non-typhoidal Salmonella isolates from laying hens in 46 farms in Uganda.
The final graph contained 22 links between risk factors and antimicrobial resistances. Solely ampicillin resistance was linked to the vaccinating person and disposal of dead birds. Systematic associations between ampicillin and sulfamethoxazole/trimethoprim and chloramphenicol, which was also linked to sulfamethoxazole/trimethoprim were detected. Sulfamethoxazole/trimethoprim was also directly linked to ciprofloxacin and trimethoprim. Trimethoprim was linked to sulfonamide and ciprofloxacin, which was also linked to sulfonamide. Tetracycline was solely linked to ciprofloxacin.
Although the results needs to be interpreted with caution due to a small data set, additive Bayesian network analysis allowed a description of a number of associations between the risk factors and antimicrobial resistances investigated.
多重耐药菌日益常见，而我们对抗菌药物耐药性复杂性的理解存在差距，部分原因是缺乏合适的统计工具。这妨碍了有效治疗，无法确定合适的干预点，且使预防变得非常困难。
我们使用加法贝叶斯网络重新分析了先前一项研究的数据。这些数据包含来自乌干达46个农场86株蛋鸡非伤寒沙门氏菌分离株对七种抗菌药物的耐药性信息以及七个潜在风险因素。
最终的图表包含风险因素与抗菌药物耐药性之间的22条联系。仅氨苄西林耐药性与疫苗接种人员和死禽处理有关。检测到氨苄西林与磺胺甲恶唑/甲氧苄啶以及氯霉素之间存在系统性关联，氯霉素也与磺胺甲恶唑/甲氧苄啶有关。磺胺甲恶唑/甲氧苄啶还直接与环丙沙星和甲氧苄啶有关。甲氧苄啶与磺胺类药物和环丙沙星有关，环丙沙星也与磺胺类药物有关。四环素仅与环丙沙星有关。
尽管由于数据集较小，结果需要谨慎解读，但加法贝叶斯网络分析能够描述所研究的风险因素与抗菌药物耐药性之间的一些关联。
