已发表论文

2016-2022 年我国某三级医院铜绿假单胞菌感染分布、药敏及动态变化趋势

 

Authors Li XY, Liu XG, Dong ZL, Chai LT, Liu YJ, Qi J, Zhao J 

Received 19 February 2023

Accepted for publication 2 May 2023

Published 3 June 2023 Volume 2023:16 Pages 3525—3533

DOI https://doi.org/10.2147/IDR.S408956

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Prof. Dr. Héctor M Mora-Montes

Background: Drug-resistant Pseudomonas aeruginosa infections rapidly increased and contributed to life-threatening nosocomial infections; however, the distribution, species, drug susceptibility and dynamic trends of P. aeruginosa infection in China remained unclear. This study was conducted to better understand the epidemiological data of increased P. aeruginosa infections from 2016 to 2022 in a hospital in China.
Methods: This study involved 3301 patients infected with P. aeruginosa , diagnosed using a nosocomial infection surveillance system in a tertiary hospital between 2016 and 2022. The P. aeruginosa infections from 2016 to 2022 were assessed according to the hospital department and species, and the drug susceptibility was evaluated using 16 antimicrobial agents.
Results: The P. aeruginosa infection prevalence in the hospital department was: Neurosurgery (14.30%), Emergency (13.30%), and Critical Care Medicine (11.69%). Samples for P. aeruginosa infection identification were from sputum (72.52%) and other secreta (9.91%). The P. aeruginosa infections demonstrated a greater sensitivity to amikacin (AMK, 91.82%), tobramycin (TOB, 82.79%), and gentamycin (GEN, 82.01%); however, P. aeruginosa infection demonstrated greater resistance to ticarcillin (22.57%), levofloxacin (21.63%), and ciprofloxacin (18.00%).
Conclusion: The P. aeruginosa infections were commonly observed in the Neurosurgery, Emergency, and Critical Care Medicine departments and demonstrated greater sensitivity to AMK, TOB, and GEN than the other drugs.
Keywords: Pseudomonas aeruginosa , distribution, drug susceptibility, dynamic trend