PDF(Pubmed)
Abstract：
UNASSIGNED: Existing breakpoint guidelines are not optimal for interpreting antimicrobial resistance (AMR) data from animal studies and low-income countries, and therefore their utility for analysing such data is limited. There is a need to integrate diverse data sets, such as those from low-income populations and animals, to improve data interpretation.
UNASSIGNED: There is very limited research on the relative merits of clinical breakpoints, epidemiological cut-offs (ECOFFs) and normalized resistance interpretation (NRI) breakpoints in interpreting microbiological data, particularly in animal studies and studies from low-income countries.
UNASSIGNED: The aim of this study was to compare antimicrobial resistance in Escherichia coli isolates using ECOFFs, CLSI and NRI breakpoints.
UNASSIGNED: A total of 59 non-repetitive poultry isolates were selected for investigation based on lactose fermentation on MacConkey agar and subsequent identification and confirmation as E. coli using chromogenic agar and uidA PCR. Kirby Bauer disc diffusion was used for susceptibility testing. For each antimicrobial agent, inhibition zone diameters were measured, and ECOFFs, CLSI and NRI bespoke breakpoints were used for resistance interpretation.
UNASSIGNED: According to the interpretation of all breakpoints except ECOFFs, tetracycline resistance was significantly higher (TET) (67.8 -69.5 %), than those for ciprofloxacin (CIPRO) (18.6 -32.2 %), imipenem (IMI) (3.4 -35 %) and ceftazidime (CEF) (1.7 -45.8 %). Prevalence estimates of AMR using CLSI and NRI bespoke breakpoints did not differ for CEF (1.7 % CB and 1.7 % COWT), IMI (3.4 % CB and 4.0 % COWT) and TET (67.8 % CB and 69.5 % COWT). However, with ECOFFs, AMR estimates for CEF, IMI and CIP were significantly higher (45.8, 35.6 and 64.4 %, respectively; P<0.05). Across all the three breakpoints, resistance to ciprofloxacin varied significantly (32.2 % CB, 64.4 % ECOFFs and 18.6 % COWT, P<0.05).
UNASSIGNED: AMR interpretation is influenced by the breakpoint used, necessitating further standardization, especially for microbiological breakpoints, in order to harmonize outputs. The AMR ECOFF estimates in the present study were significantly higher compared to CLSI and NRI.
UNASSIGNED: There is very limited research on the relative merits of clinical breakpoints, epidemiological cut-offs (ECOFFs) and normalized resistance interpretation (NRI) breakpoints in interpreting microbiological data, particularly in animal studies and studies from low-income countries.
UNASSIGNED: The aim of this study was to compare antimicrobial resistance in Escherichia coli isolates using ECOFFs, CLSI and NRI breakpoints.
UNASSIGNED: A total of 59 non-repetitive poultry isolates were selected for investigation based on lactose fermentation on MacConkey agar and subsequent identification and confirmation as E. coli using chromogenic agar and uidA PCR. Kirby Bauer disc diffusion was used for susceptibility testing. For each antimicrobial agent, inhibition zone diameters were measured, and ECOFFs, CLSI and NRI bespoke breakpoints were used for resistance interpretation.
UNASSIGNED: According to the interpretation of all breakpoints except ECOFFs, tetracycline resistance was significantly higher (TET) (67.8 -69.5 %), than those for ciprofloxacin (CIPRO) (18.6 -32.2 %), imipenem (IMI) (3.4 -35 %) and ceftazidime (CEF) (1.7 -45.8 %). Prevalence estimates of AMR using CLSI and NRI bespoke breakpoints did not differ for CEF (1.7 % CB and 1.7 % COWT), IMI (3.4 % CB and 4.0 % COWT) and TET (67.8 % CB and 69.5 % COWT). However, with ECOFFs, AMR estimates for CEF, IMI and CIP were significantly higher (45.8, 35.6 and 64.4 %, respectively; P<0.05). Across all the three breakpoints, resistance to ciprofloxacin varied significantly (32.2 % CB, 64.4 % ECOFFs and 18.6 % COWT, P<0.05).
UNASSIGNED: AMR interpretation is influenced by the breakpoint used, necessitating further standardization, especially for microbiological breakpoints, in order to harmonize outputs. The AMR ECOFF estimates in the present study were significantly higher compared to CLSI and NRI.
摘要：
■现有的断点指南对于解释动物研究和低收入国家的抗菌素耐药性（AMR）数据并不理想。因此，它们用于分析这些数据的效用是有限的。有必要整合不同的数据集，比如低收入人群和动物，改善数据解释。
■关于临床断点的相对优点的研究非常有限，在解释微生物数据时，流行病学截止点（ECOFFs）和标准化耐药性解释（NRI）断点，特别是在动物研究和低收入国家的研究中。
■本研究的目的是使用ECOFF比较大肠杆菌分离株的抗菌素耐药性，CLSI和NRI断点。
■基于在MacConkey琼脂上的乳糖发酵以及随后使用显色琼脂和uidAPCR鉴定和确认为大肠杆菌,选择总共59种非重复家禽分离物用于研究。使用KirbyBauer圆盘扩散进行敏感性测试。对于每种抗菌剂，测量抑制区直径，和ECOFF，CLSI和NRI定制断点用于抗性解释。
■根据除ECOFF以外的所有断点的解释，四环素耐药率（TET）明显更高（67.8-69.5％），比环丙沙星（CIPRO）（18.6-32.2％），亚胺培南（IMI）（3.4-35％）和头孢他啶（CEF）（1.7-45.8％）。使用CLSI和NRI定制断点的AMR患病率估计对于CEF(1.7%CB和1.7%COWT)没有差异，IMI（3.4%CB和4.0%COWT）和TET（67.8%CB和69.5%COWT）。然而,ECOFF,CEF的AMR估计，IMI和CIP显著高于(45.8%、35.6%和64.4%，分别；P<0.05）。在所有三个断点中，对环丙沙星的耐药性差异显著(32.2%CB，64.4%的ECOFF和18.6%的COWT，P<0.05)。
■AMR解释受所用断点的影响，需要进一步标准化，特别是微生物断点，以协调产出。与CLSI和NRI相比，本研究中的AMRECOFF估计值明显更高。
■关于临床断点的相对优点的研究非常有限，在解释微生物数据时，流行病学截止点（ECOFFs）和标准化耐药性解释（NRI）断点，特别是在动物研究和低收入国家的研究中。
■本研究的目的是使用ECOFF比较大肠杆菌分离株的抗菌素耐药性，CLSI和NRI断点。
■基于在MacConkey琼脂上的乳糖发酵以及随后使用显色琼脂和uidAPCR鉴定和确认为大肠杆菌,选择总共59种非重复家禽分离物用于研究。使用KirbyBauer圆盘扩散进行敏感性测试。对于每种抗菌剂，测量抑制区直径，和ECOFF，CLSI和NRI定制断点用于抗性解释。
■根据除ECOFF以外的所有断点的解释，四环素耐药率（TET）明显更高（67.8-69.5％），比环丙沙星（CIPRO）（18.6-32.2％），亚胺培南（IMI）（3.4-35％）和头孢他啶（CEF）（1.7-45.8％）。使用CLSI和NRI定制断点的AMR患病率估计对于CEF(1.7%CB和1.7%COWT)没有差异，IMI（3.4%CB和4.0%COWT）和TET（67.8%CB和69.5%COWT）。然而,ECOFF,CEF的AMR估计，IMI和CIP显著高于(45.8%、35.6%和64.4%，分别；P<0.05）。在所有三个断点中，对环丙沙星的耐药性差异显著(32.2%CB，64.4%的ECOFF和18.6%的COWT，P<0.05)。
■AMR解释受所用断点的影响，需要进一步标准化，特别是微生物断点，以协调产出。与CLSI和NRI相比，本研究中的AMRECOFF估计值明显更高。
