| 引用本文: |
焦芳艳,尹铁球,黄露萍,李勇,谭宇蓉.2016-2018年临床分离铜绿假单胞菌的耐药情况分析[J].湖南中医药大学学报,2019,39(6):758-762[点击复制] |
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| 2016-2018年临床分离铜绿假单胞菌的耐药情况分析 |
| 焦芳艳,尹铁球,黄露萍,李勇,谭宇蓉 |
| (中南大学湘雅基础医学院, 湖南 长沙 410078;湖南省脑科医院, 湖南 长沙 410007) |
| 摘要: |
| 目的 分析2016年至2018年湖南省脑科医院铜绿假单胞菌的临床分布情况、耐药情况以及耐药菌株Ⅰ类整合子基因。方法 选取湖南省脑科医院2016年1月1日至2018年12月31日临床送检各类标本中分离出795株铜绿假单胞菌作为分析对象，就铜绿假单胞菌的临床分布情况以及耐药情况统计分析，2018年ICU分离的13株多重耐药菌株采用PCR扩增检测Ⅰ类整合子。结果 铜绿假单胞菌分布科室主要为神经外科（24.53%），其次为呼吸内科（22.26%）和重症医学科（13.21%）；铜绿假单胞菌对临床常用的20种抗生素耐药率和敏感率0-100%不等，多重耐药呈上升趋势；13株多重耐药菌株6株Ⅰ类整合子阳性。结论 及时统计细菌分布情况、药物的耐药率、敏感率，并对其进行分析，可以为临床合理用药提供依据，有效预防和控制感染。 |
| 关键词: 铜绿假单胞菌 抗菌药物 耐药率 敏感率 |
| DOI：10.3969/j.issn.1674-070X.2019.06.019 |
| 投稿时间：2019-03-19 |
| 基金项目:湖南省卫生健康委计划项目（B2016026）。 |
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| Analysis of Drug-resistance of Separated Pseudomonas Aeruginosa in Clinics in 2016-2018 |
| JIAO Fangyan,YIN Tieqiu,HUANG Luping,LI Yong,TAN Yurong |
| (Xiangya College of Basic Medicine of Central South University, Changsha, Hunan 410078 China;Brain Hospital of Hunan Province, Changsha, Hunan 410007, China) |
| Abstract: |
| Objective To analyze the clinical distribution, drug-resistance and class I integron genes of drug-resistant strains of pseudomonas aeruginosa (PA) in the Brain Hospital of Hunan Province from 2016 to 2018. Methods A total of 795 PA separated from clinical specimens submitted for examination samples in the Brain Hospital of Hunan Province from January 1, 2016 to December 31, 2018 were regarded as analysis objects. The clinical distribution and drug-resistance of PA were statistically analyzed. In 2018, class I integron of 13 multiple drug-resistant strains separated from specimens submitted by ICU were detected by PCR amplification. Results Most of PA was from neurosurgery department (24.53%), followed by the department of respiratory medicine (22.26%) and the department of critical care medicine (13.21%). The drug-resistance rate and susceptibility rate of PA to 20 antibiotics commonly used in clinic ranged from 0-100%, with multiple drug-resistance on the rise. The class I integrons were detected positive in 6 of the 13 multiple drug-resistant strains. Conclusion Timely statistics and analysis of bacterial distribution, drug-resistance rate and susceptibility rate could provide the basis for rational drug use in clinics and effectively prevent and control infection. |
| Key words: pseudomonas aeruginosa antibacterial drug drug-resistance rate susceptibility rate |
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