Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY.
Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY.
Am J Vet Res. 2023 Nov 13;84(12). doi: 10.2460/ajvr.23.09.0216. Print 2023 Dec 1.
This study aims to assess the antimicrobial resistance (AMR) trends among Escherichia coli isolated from cats between 2008 and 2022, utilizing MIC data, within a one-health framework.
The study analyzed MIC results from 1,477 feline E coli isolates that were obtained from samples submitted to the Cornell University Animal Health Diagnostic Center, primarily from the northeastern US.
MIC values were categorized as susceptible or not susceptible using the Clinical and Laboratory Standards Institute breakpoints. Multidrug resistance (MDR) was analyzed using a Poisson regression model. Additionally, accelerated failure time models were employed to analyze MIC values.
Out of the 1,477 E coli isolates examined, 739 (50%) showed susceptibility to all tested antimicrobials. Among the tested antimicrobials, cefazolin (69%) and ampicillin (74% for urinary tract isolates) exhibited the lowest susceptibility. Overall, 15% of isolates were not susceptible to cefovecin. E coli isolates were highly susceptible (> 95%) to antibiotics typically reserved for human use. Almost one-third of the isolates were classified as MDR, with nonurinary isolates more likely to exhibit an MDR pattern. A decrease in MICs for fluoroquinolones and gentamicin in recent years was identified. However, MICs for cephalexin increased from 2016 to 2022 and cefovecin from 2012 to 2019.
This study highlights the challenge of AMR in feline medicine, emphasizing the importance of responsible antimicrobial use and surveillance to address E coli AMR. The related Currents in One Health by Cazer et al, JAVMA, December 2023, addresses additional feline antimicrobial stewardship topics.
本研究旨在利用 MIC 数据，在一个大健康框架下，评估 2008 年至 2022 年间猫源大肠杆菌的抗菌药物耐药（AMR）趋势。
该研究分析了来自康奈尔大学动物健康诊断中心的 1477 株猫源大肠杆菌分离株的 MIC 结果，这些分离株主要来自美国东北部，样本来自临床送检。
采用临床和实验室标准协会的折点将 MIC 值归类为敏感或不敏感。使用泊松回归模型分析多药耐药（MDR）。此外，还采用加速失效时间模型分析 MIC 值。
在所研究的 1477 株大肠杆菌分离株中，739 株（50%）对所有测试的抗菌药物均表现出敏感性。在测试的抗菌药物中，头孢唑林（69%）和氨苄西林（尿路感染分离株的 74%）的敏感性最低。总体而言，15%的分离株对头孢噻呋钠不敏感。大肠杆菌分离株对通常用于人类的抗生素高度敏感（>95%）。近三分之一的分离株被归类为 MDR，非尿路感染分离株更有可能表现出 MDR 模式。近年来，氟喹诺酮类药物和庆大霉素的 MIC 值有所下降。然而，头孢氨苄的 MIC 值从 2016 年到 2022 年增加，头孢噻呋的 MIC 值从 2012 年到 2019 年增加。
本研究强调了猫科动物医学中 AMR 的挑战，强调了负责任的抗菌药物使用和监测以解决大肠杆菌 AMR 的重要性。相关的 Currents in One Health 由 Cazer 等人撰写，发表于 JAVMA，2023 年 12 月，涉及其他猫科动物抗菌药物管理主题。
