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埃塞俄比亚对抗菌药物的耐药性:一项荟萃分析。

Resistance of to antimicrobial agents in Ethiopia: a meta-analysis.

作者信息

Deyno Serawit, Fekadu Sintayehu, Astatkie Ayalew

机构信息

Department of Pharmacology, School of Medicine, College of Medicine and Health Sciences, Hawassa University, P. O. Box 1560, Hawassa, Ethiopia.

Department of Microbiology, Faculty of Medicine, Shimane University, Shimane, Japan.

出版信息

Antimicrob Resist Infect Control. 2017 Aug 23;6:85. doi: 10.1186/s13756-017-0243-7. eCollection 2017.

DOI:10.1186/s13756-017-0243-7
PMID:28852476
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5569497/
Abstract

BACKGROUND

Emergence of antimicrobial resistance by has limited treatment options against its infections. The purpose of this study was to determine the pooled prevalence of resistance to different antimicrobial agents by in Ethiopia.

METHODS

Web-based search was conducted in the databases of PubMed, Google Scholar, Hinari, Scopus and the Directory of Open Access Journals (DOAJ) to identify potentially eligible published studies. Required data were extracted and entered into Excel spread sheet. Statistical analyses were performed using Stata version 13.0. The Stata command was used to pool prevalence values. Twenty-one separate meta-analysis were done to estimate the pooled prevalence of the resistance of to twenty-one different antimicrobial agents. Heterogeneity among the studies was assessed using the I statistic and chi-square test. Publication bias was assessed using Egger's test. Because of significant heterogeneity amongst the studies, the random effects model was used to pool prevalence values.

RESULTS

The electronic database search yielded 1317 studies among which 45 studies met our inclusion criteria. Our analyses demonstrated very high level of resistance to amoxicillin (77% [95% confidence interval (CI): 68%, 0.85%]), penicillin (76% [95% CI: 67%, 84%]), ampicillin (75% [95% CI: 65%, 85%]), tetracycline (62% [95% CI: 55%, 68%]), methicillin (47% [95% CI: 33%, 61%]), cotrimoxaziole (47% [95% CI: 40%, 55%]), doxycycline (43% [95% CI: 26%, 60%]), and erythromycin (41% [95% CI: 29%, 54%]). Relatively low prevalence of resistance was observed with kanamycin (14% [95% CI: 5%, 25%]) and ciprofloxacin (19% [95% CI: 13%, 26%]). The resistance level to vancomycin is 11% 995% CI: (4%, 20%). High heterogeneity was observed for each of the meta-analysis performed (I ranging from 79.36% to 95.93%; all -values ≤0.01). Eggers' test did not show a significant publication bias for all antimicrobial agents except for erythromycin and ampicillin.

CONCLUSIONS

in Ethiopia has gotten notoriously resistant to almost to all of antimicrobial agents in use including, penicillin, cephalosporins, tetracyclines, chloramphenicol, methicillin, vancomycin and sulphonamides. The resistance level to vancomycin is bothersome and requires a due attention. Continued and multidimensional efforts of antimicrobial stewardship program promoting rational use of antibiotics, infection prevention and containment of AMR are urgently needed.

摘要

背景

[病原体名称]出现的抗菌药物耐药性限制了针对其感染的治疗选择。本研究的目的是确定埃塞俄比亚[病原体名称]对不同抗菌药物的合并耐药率。

方法

在PubMed、谷歌学术、Hinari、Scopus和开放获取期刊目录(DOAJ)数据库中进行基于网络的搜索,以识别潜在符合条件的已发表研究。提取所需数据并输入Excel电子表格。使用Stata 13.0版本进行统计分析。使用Stata命令合并患病率值。进行了21项单独的荟萃分析,以估计[病原体名称]对21种不同抗菌药物的合并耐药率。使用I统计量和卡方检验评估研究之间的异质性。使用Egger检验评估发表偏倚。由于研究之间存在显著异质性,因此使用随机效应模型合并患病率值。

结果

电子数据库搜索产生了1317项研究,其中45项研究符合我们的纳入标准。我们的分析表明,对阿莫西林的耐药水平非常高(77%[95%置信区间(CI):68%,85%])、青霉素(76%[95%CI:67%,84%])、氨苄西林(75%[95%CI:65%,85%])、四环素(62%[95%CI:55%,68%])、甲氧西林(47%[95%CI:33%,61%])、复方新诺明(47%[95%CI:40%,55%])、强力霉素(43%[95%CI:26%,60%])和红霉素(41%[95%CI:29%,54%])。观察到卡那霉素(14%[95%CI:5%,25%])和环丙沙星(19%[95%CI:13%,26%])的耐药率相对较低。对万古霉素的耐药水平为11%[95%CI:(4%,20%)]。对每项进行的荟萃分析都观察到高度异质性(I范围从79.36%到95.93%;所有P值≤0.01)。除红霉素和氨苄西林外,Egger检验未显示所有抗菌药物存在显著的发表偏倚。

结论

在埃塞俄比亚,[病原体名称]对几乎所有使用的抗菌药物都具有极高的耐药性,包括青霉素、头孢菌素、四环素、氯霉素、甲氧西林、万古霉素和磺胺类药物。对万古霉素的耐药水平令人担忧,需要给予应有的关注。迫切需要持续和多方面的抗菌药物管理计划,以促进抗生素的合理使用、感染预防和抗菌药物耐药性的控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/7eebd8749790/13756_2017_243_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/e4019c120234/13756_2017_243_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/6c72dcfd04a6/13756_2017_243_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/146f05b34271/13756_2017_243_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/1996698e6b60/13756_2017_243_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/41cf2dce523b/13756_2017_243_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/1418aa5f3034/13756_2017_243_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/34033765d8e8/13756_2017_243_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/7eebd8749790/13756_2017_243_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/e4019c120234/13756_2017_243_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/146966f5c810/13756_2017_243_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/6c72dcfd04a6/13756_2017_243_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/146f05b34271/13756_2017_243_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/1996698e6b60/13756_2017_243_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/41cf2dce523b/13756_2017_243_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/1418aa5f3034/13756_2017_243_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/34033765d8e8/13756_2017_243_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/367e/5569497/7eebd8749790/13756_2017_243_Fig9_HTML.jpg

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