Suppr超能文献

伤口感染患者中多重耐药菌的分离及其抗生素敏感性模式:一项横断面研究。

Isolation of multidrug resistance bacteria from the patients with wound infection and their antibiotics susceptibility patterns: A cross-sectional study.

作者信息

Nobel Fahim Alam, Islam Saiful, Babu Golap, Akter Sharmin, Jebin Ruksana Akter, Sarker Titash Chandra, Islam Ashekul, Islam Mohammod Johirul

机构信息

Department of Biochemistry and Molecular Biology, Mawlana Bhashani Science and Technology University, Santosh, Tangail, 1902, Bangladesh.

Department of Biochemistry and Molecular Biology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.

出版信息

Ann Med Surg (Lond). 2022 Nov 14;84:104895. doi: 10.1016/j.amsu.2022.104895. eCollection 2022 Dec.

Abstract

INTRODUCTION

Antimicrobial resistance has become one of the most severe public problems in both developed and developing countries like Bangladesh. In this study, several multi-drug resistant bacteria were isolated from the wound infections and demonstrated their antibiotic susceptibility pattern in Bangladeshi patients.

METHODS

A total of 699 bacterial isolates were collected from wound swabs and each isolate was identified using gram staining, biochemical assays, antibiotic susceptibility tests with the disk diffusion method, and colony morphology. Samples were taken from January 2018 to December 2019. The analysis was conducted using SPSS (Inc., Chicago, IL, USA), and descriptive statistics were employed to illustrate the findings.

RESULTS

We have found 14.4% gram-positive bacteria (n = 100) and 85.6% gram-negative bacteria (n = 595) among the 695 samples by gram staining methods. The most prevalent gram-positive and gram-negative bacteria present in wound infections were Staphylococcus spp. (81.5%) and Pseudomonas spp. (89%), respectively. Antimicrobials that were mostly resistant to gram-negative isolates were Amoxicillin (75.8%), Cefixime (75.5%), Cefuroxime (70.3%), and Ceftazidime (69.6%). On the other hand, cefixime and ceftazidime accounted for 73% of the resistance against gram-positive isolates, followed by amoxicillin (71%), and penicillin-G (69%). Meropenem was found to be the most sensitive antibiotic for gram-negative bacteria. Meropenem and Gentamycin were found to have a percentage of sensitivity for gram-positive bacteria. Based on the assessment of 13 different antimicrobial classes, the percentage of multi-drug resistant bacteria identified in gram-negative bacteria was 84% and in gram-positive bacteria was 79%. Among gram-negative bacterial isolates, 82% pseudomonas spp, 88.5% Klebsiella spp, and 91.6% Proteus spp were reported as multi-drug resistant. On the other hand, Pseudomonas spp, Klebsiella spp, and Proteus spp. were found to be multi-drug resistant in 82%, 88.5%, and 91.6% of gram-negative bacterial isolates, respectively. It was shown that staphylococcus aureus (81%) and staphylococcus spp (78.6%) became gram-positive among gram-positive isolates.

CONCLUSION

According to this study, frequently isolated bacteria have a high frequency of MDR, which is the most pressing issue in public health. This study helps to manage the evidence-based treatment strategy and the urgency of early identification of drug-resistant bacteria that can reduce disease burden.

摘要

引言

在孟加拉国等发达国家和发展中国家,抗菌药物耐药性已成为最严重的公共问题之一。在本研究中,从伤口感染中分离出几种多重耐药细菌,并展示了它们在孟加拉国患者中的抗生素敏感性模式。

方法

从伤口拭子中总共收集了699株细菌分离株,并通过革兰氏染色、生化分析、纸片扩散法抗生素敏感性测试和菌落形态对每株分离株进行鉴定。样本采集时间为2018年1月至2019年12月。使用SPSS(美国伊利诺伊州芝加哥市SPSS公司)进行分析,并采用描述性统计来说明研究结果。

结果

通过革兰氏染色法,在695个样本中,我们发现革兰氏阳性菌占14.4%(n = 100),革兰氏阴性菌占85.6%(n = 595)。伤口感染中最常见的革兰氏阳性菌和革兰氏阴性菌分别是葡萄球菌属(81.5%)和假单胞菌属(89%)。对革兰氏阴性菌分离株耐药性最高的抗菌药物是阿莫西林(75.8%)、头孢克肟(75.5%)、头孢呋辛(70.3%)和头孢他啶(69.6%)。另一方面,头孢克肟和头孢他啶对革兰氏阳性菌分离株的耐药率为73%,其次是阿莫西林(71%)和青霉素G(69%)。美罗培南被发现是对革兰氏阴性菌最敏感的抗生素。美罗培南和庆大霉素对革兰氏阳性菌也有一定的敏感率。基于对13种不同抗菌药物类别的评估,革兰氏阴性菌中鉴定出多重耐药菌的比例为84%,革兰氏阳性菌中为79%。在革兰氏阴性菌分离株中,82%的假单胞菌属、88.5%的克雷伯菌属和91.6%的变形杆菌属被报告为多重耐药。另一方面,在革兰氏阴性菌分离株中,分别有82%、88.5%和91.6%的假单胞菌属、克雷伯菌属和变形杆菌属被发现是多重耐药的。结果表明,在革兰氏阳性菌分离株中,金黄色葡萄球菌(81%)和葡萄球菌属(78.6%)为革兰氏阳性菌。

结论

根据本研究,常见分离细菌的多重耐药率很高,这是公共卫生中最紧迫的问题。本研究有助于制定基于证据的治疗策略以及尽早识别可减轻疾病负担的耐药细菌的紧迫性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e9a/9758378/33c71f5c7a31/gr1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验