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用于区分耐碳青霉烯类与敏感肠杆菌科菌株的近红外光谱评估

Near-Infrared Spectroscopy Evaluations for the Differentiation of Carbapenem-Resistant from Susceptible Enterobacteriaceae Strains.

作者信息

Alharbi Bushra, Sikulu-Lord Maggy, Lord Anton, Zowawi Hosam M, Trembizki Ella

机构信息

The University of Queensland Centre for Clinical Research, Faculty of Medicine, Brisbane 4029, Queensland, Australia.

Faculty of Pharmacy, Taibah University, Madinah 20012, Saudi Arabia.

出版信息

Diagnostics (Basel). 2020 Sep 23;10(10):736. doi: 10.3390/diagnostics10100736.

Abstract

Antimicrobial Resistance (AMR) caused by Carbapenem-Resistant Enterobacteriaceae (CRE) is a global threat. Accurate identification of these bacterial species with associated AMR is critical for their management. While highly accurate methods to detect CRE are available, they are costly, timely and require expert skills, making their application infeasible in low-resource settings. Here, we investigated the potential of Near-Infrared Spectroscopy (NIRS) for a range of applications: (i) the detection and differentiation of isolates of two pathogenic Enterobacteriaceae species, and , and (ii) the differentiation of carbapenem resistant and susceptible . NIRS has successfully differentiated between and isolates with a predictive accuracy of 89.04% (95% CI; 88.7-89.4%). isolates harbouring carbapenem-resistance determinants were differentiated from susceptible strains with an accuracy of 85% (95% CI; 84.2-86.1%). To our knowledge, this is the largest proof of concept demonstration for the utility and feasibility of NIRS to rapidly differentiate between and as well as carbapenem-resistant from susceptible strains.

摘要

耐碳青霉烯类肠杆菌科细菌(CRE)引起的抗菌药物耐药性(AMR)是一个全球性威胁。准确识别这些具有相关AMR的细菌物种对于其管理至关重要。虽然有检测CRE的高度准确方法,但它们成本高、耗时且需要专业技能,这使得它们在资源匮乏地区无法应用。在此,我们研究了近红外光谱(NIRS)在一系列应用中的潜力:(i)检测和区分两种致病性肠杆菌科细菌的分离株,以及(ii)区分耐碳青霉烯类和敏感的。NIRS已成功区分和分离株,预测准确率为89.04%(95%CI;88.7-89.4%)。携带耐碳青霉烯类决定簇的分离株与敏感菌株的区分准确率为85%(95%CI;84.2-86.1%)。据我们所知,这是关于NIRS快速区分和以及耐碳青霉烯类与敏感菌株的实用性和可行性的最大概念验证演示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f390/7598181/f8e2a73081d4/diagnostics-10-00736-g001a.jpg

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