Gomez Diego E, Arroyo Luis G, Poljak Zvonimir, Viel Laurent, Weese J Scott
Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, Ontario N1G 2W1, Canada.
Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, Ontario N1G 2W1, Canada.
Vet J. 2017 Aug;226:15-25. doi: 10.1016/j.tvjl.2017.06.009. Epub 2017 Jul 8.
This study evaluated the impact of an algorithm targeting antimicrobial therapy of diarrhoeic calves on the incidence of diarrhoea, antimicrobial treatment rates, overall mortality, mortality of diarrhoeic calves and changes in the faecal microbiota. The algorithm was designed to target antimicrobial therapy in systemically ill calves from on two dairy farms. Retrospective (farm 1: 529 calves; farm 2: 639 calves) and prospective (farm 1: 639 calves; farm 2: 842 calves) cohorts were examined for 12 months before and after implementation of the algorithm. The Mantel-Haenszel test and Kaplan-Meier survival curves were used to assess the cumulative incidence risk (CIR) and time to development of each outcome before and after implementation of the algorithm. The CIR of antimicrobial treatment rates was 80% lower after implementation of the algorithm on both farms (CIR 0.19, 95% confidence interval 0.17-0.21). There was no difference in the CIR of overall mortality, but the CRI for mortality of diarrhoeic calves was lower in the period after implementation of the algorithm on one farm. The faecal microbiota of 15 healthy calves from both farms at each time period were characterised using a sequencing platform targeting the V4 region of the 16S rRNA gene. On both farms, there were significant differences in community membership and structure (parsimony P<0.001). Use of the algorithm for treatment of diarrhoeic calves reduced antimicrobial treatment rates without a negative impact on the health of calves. However, the experimental design did not take into account the potential confounding effects of dietary changes between the study periods.
本研究评估了一种针对腹泻犊牛抗菌治疗的算法对腹泻发病率、抗菌治疗率、总体死亡率、腹泻犊牛死亡率以及粪便微生物群变化的影响。该算法旨在针对两个奶牛场患有全身性疾病的犊牛进行抗菌治疗。在算法实施前后,对回顾性队列(农场1:529头犊牛;农场2:639头犊牛)和前瞻性队列(农场1:639头犊牛;农场2:842头犊牛)进行了为期12个月的检查。使用Mantel-Haenszel检验和Kaplan-Meier生存曲线来评估算法实施前后各结局的累积发病风险(CIR)和发生时间。在两个农场实施该算法后,抗菌治疗率的CIR降低了80%(CIR为0.19,95%置信区间为0.17 - 0.21)。总体死亡率的CIR没有差异,但在一个农场实施该算法后的时期内,腹泻犊牛死亡率的CRI较低。使用针对16S rRNA基因V4区域的测序平台对两个农场在每个时间段的15头健康犊牛的粪便微生物群进行了特征分析。在两个农场,群落组成和结构均存在显著差异(简约性P<0.001)。使用该算法治疗腹泻犊牛可降低抗菌治疗率,且对犊牛健康无负面影响。然而,实验设计未考虑研究期间饮食变化的潜在混杂效应。