Literature DB >> 30904685

Effects of laboratory capabilities on combating antimicrobial resistance, 2013-2016: A static model panel data analysis.

Youwen Cui1, Junjie Liu1, Xinping Zhang2.   

Abstract

OBJECTIVES: Antimicrobial resistance (AMR) has become a serious global public health problem. The World Health Organization (WHO) and European Union (EU) have taken actions to combat this issue, in which laboratory capability construction is a crucial part. This study aimed to explore the relationship between laboratory capabilities and antimicrobial resistance from a macro perspective.
METHODS: The study used annual national level penal data from the EU Laboratory Capability Monitoring System and Antimicrobial Resistance Surveillance Europe 2013-2016. A conventional static panel data analysis was constructed to establish the relationship between the antimicrobial resistance rates and laboratory capabilities.
RESULTS: Laboratory capability on antimicrobial drug resistance characterisation and monitoring (LC8) showed a positive effect on Escherichia coli (E. coli) combined resistance rate (Y5), E. coli resistant rate of aminoglycosides (Y4), and Klebsiella pneumoniae resistant rate of carbapenems (Y8) (OR=0.929, 0.957, and 0.861; P=0.035, 0.007, and 0.026, respectively). However, following the diagnostic testing guidelines (LC2) caused higher resistance rates of Klebsiella pneumoniae to fluoroquinolones (Y6), third-generation cephalosporins (Y7), and aminoglycosides (Y9) (OR=1.076, 1.093, and1.065; P=0.011, 0.032, and 0.002, respectively).
CONCLUSIONS: Antimicrobial drug resistance characterisation and monitoring by laboratories has contributed to minimising antimicrobial resistance, while the mechanism of laboratory capabilities to pose an ineffective or negative impact on AMR remains to be further studied.
Copyright © 2019 International Society for Antimicrobial Chemotherapy. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Antimicrobial resistance; Laboratory capability/capacity; Panel data

Year:  2019        PMID: 30904685     DOI: 10.1016/j.jgar.2019.03.007

Source DB:  PubMed          Journal:  J Glob Antimicrob Resist        ISSN: 2213-7165            Impact factor:   4.035


  4 in total

1.  Appropriateness of Empirical Fluoroquinolones Therapy in Patients Infected with Escherichia coli, Klebsiella pneumoniae, or Pseudomonas aeruginosa: The Importance of the CLSI Breakpoints Revision.

Authors:  Ying Wang; Xinping Zhang; Xuemei Wang; Xiaoquan Lai
Journal:  Infect Drug Resist       Date:  2021-08-31       Impact factor: 4.003

2.  Estimating Factors Related to Fluoroquinolone Resistance Based on One Health Perspective: Static and Dynamic Panel Data Analyses From Europe.

Authors:  Dandan Zhang; Youwen Cui; Xinping Zhang
Journal:  Front Pharmacol       Date:  2019-10-03       Impact factor: 5.810

3.  Information Complexity and Behavior Intention to Prescribe Antibiotics Based on the Antimicrobial Susceptibility Testing Report: The Mediating Roles of Information Overload and Attitude.

Authors:  Ying Wang; Xinping Zhang; Qian Zhou; Xiaojun Xu; Xiaofeng Liu; Shaohui Lu
Journal:  Front Pharmacol       Date:  2021-11-10       Impact factor: 5.810

4.  Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans.

Authors:  David Emes; Nichola Naylor; Jeff Waage; Gwenan Knight
Journal:  Antibiotics (Basel)       Date:  2022-01-06
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.