Lyu Jingwen, Chen Huimin, Bao Jinwei, Liu Suling, Chen Yiling, Cui Xuxia, Guo Caixia, Gu Bing, Li Lu
Department of Clinical Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510000, China.
Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523808, China.
J Clin Med. 2023 Feb 2;12(3):1189. doi: 10.3390/jcm12031189.
The aim of the current study was to analyse the distribution of antimicrobial drug resistance (AMR) among (, PA) isolates from Guangdong Provincial People's Hospital (GDPH) from 2017 to 2021, and the impact of the COVID-19 outbreak on changes in the clinical distribution and drug resistance rate of to establish guidelines for empiric therapy. Electronic clinical data registry records from 2017 to 2021 were retrospectively analysed to study the AMR among strains from GDPH. The strains were identified by VITEK 2 Compact and MALDI-TOF MS, MIC method or Kirby-Bauer method for antibiotic susceptibility testing. The results were interpreted according to the CLSI 2020 standard, and the data were analysed using WHONET 5.6 and SPSS 23.0 software. A total of 3036 strains were detected in the hospital from 2017 to 2021, and they were primarily distributed in the ICU (n = 1207, 39.8%). The most frequent specimens were respiratory tract samples (59.6%). The detection rate for in 5 years was highest in September, and the population distribution was primarily male(68.2%). For the trend in the drug resistance rate, the 5-year drug resistance rate of imipenem (22.4%), aztreonam (21.5%) and meropenem (19.3%) remained at high levels. The resistance rate of cefepime decreased from 9.4% to 4.8%, showing a decreasing trend year by year ( < 0.001). The antibiotics with low resistance rates were aminoglycoside antibiotics, which were gentamicin (4.4%), tobramycin (4.3%), and amikacin (1.4%), but amikacin showed an increasing trend year by year ( = 0.008). Our analysis indicated that the detection rate of clinically resistant strains showed an upwards trend, and the number of multidrug-resistant (MDR) strains increased year by year, which will lead to stronger pathogenicity and mortality. However, after the outbreak of COVID-19 in 2020, the growth trend in the number of MDR bacteria slowed, presumably due to the strict epidemic prevention and control measures in China. This observation suggests that we should reasonably use antibiotics and treatment programs in the prevention and control of infection. Additionally, health prevention and control after the outbreak of the COVID-19 epidemic (such as wearing masks, washing hands with disinfectant, etc., which reduced the prevalence of drug resistance) led to a slowdown in the growth of the drug resistance rate of in hospitals, effectively reducing the occurrence and development of drug resistance, and saving patient's treatment costs and time.
本研究旨在分析2017年至2021年广东省人民医院(GDPH)分离的肺炎克雷伯菌(Kp)菌株的抗菌药物耐药性(AMR)分布情况,以及新冠疫情对Kp临床分布和耐药率变化的影响,以制定经验性治疗指南。回顾性分析2017年至2021年的电子临床数据登记记录,以研究GDPH的Kp菌株中的AMR情况。通过VITEK 2 Compact和MALDI-TOF MS鉴定菌株,采用MIC法或 Kirby-Bauer法进行抗生素敏感性测试。结果根据CLSI 2020标准进行解读,并使用WHONET 5.6和SPSS 23.0软件进行数据分析。2017年至2021年期间,医院共检测到3036株Kp菌株,主要分布在重症监护病房(n = 1207,39.8%)。最常见的标本是呼吸道样本(59.6%)。5年中Kp的检出率在9月最高,人群分布主要为男性(68.2%)。关于耐药率趋势,亚胺培南的5年耐药率(22.4%)、氨曲南(21.5%)和美罗培南(19.3%)仍处于较高水平。头孢吡肟的耐药率从9.4%降至4.8%,呈逐年下降趋势(P < 0.001)。耐药率较低的抗生素是氨基糖苷类抗生素,分别为庆大霉素(4.4%)、妥布霉素(4.3%)和阿米卡星(1.4%),但阿米卡星呈逐年上升趋势(P = 0.008)。我们的分析表明,临床耐药Kp菌株的检出率呈上升趋势,多重耐药(MDR)菌株数量逐年增加,这将导致更强的致病性和死亡率。然而,2020年新冠疫情爆发后,MDR细菌数量的增长趋势放缓,可能是由于中国严格的疫情防控措施。这一观察结果表明,在预防和控制Kp感染方面,我们应合理使用抗生素和治疗方案。此外,新冠疫情爆发后的卫生防控措施(如戴口罩、用消毒剂洗手等,降低了耐药性的流行)导致医院内Kp耐药率的增长放缓,有效减少了耐药性的发生和发展,节省了患者的治疗成本和时间。