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埃塞俄比亚的抗生素使用与耐药模式:系统评价与荟萃分析

Antibiotic Use and Resistance Pattern in Ethiopia: Systematic Review and Meta-Analysis.

作者信息

Muhie Oumer Abdu

机构信息

Internist, Assistant Professor of Internal Medicine, CMHS, Department of Internal Medicine, University of Gondar, Northwest, Gondar, Ethiopia.

出版信息

Int J Microbiol. 2019 Aug 1;2019:2489063. doi: 10.1155/2019/2489063. eCollection 2019.

DOI:10.1155/2019/2489063
PMID:31467550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6701335/
Abstract

BACKGROUND

In the last decades, medicines have had an unprecedented positive effect on health, leading to reduced mortality and disease burden and consequently to an improved quality of life. The rapid and ongoing spread of antimicrobial-resistant organisms threatens our ability to successfully treat a growing number of infectious diseases. In the absence of the development of new generations of antibiotic drugs, appropriate use of existing antibiotics is needed to ensure the long-term availability of effective treatment for bacterial infections. Irrational use of antibiotics is an ongoing global public health problem that deserves more attention. This review is conducted to evaluate the prevalence of inappropriate antibiotic utilization and resistance to antibiotics in Ethiopia.

METHODS

Electronic search in PubMed/MEDLINE and Google was used to find published literature with reference lists of relevant articles searched manually. Titles and abstracts were initially screened for eligibility. The full texts of articles judged to be eligible were reviewed if they meet the inclusion criteria. Data were extracted on important variables like the sample size, region of the study, the inappropriate antibiotic use, bacterial detection rate, multidrug resistance pattern, and more other variables. Microsoft Excel was used for data extraction. Quantitative analysis was performed using STATA version 11.

RESULTS

The electronic searches identified 193 articles of which 33 were found eligible. The random-effects model was used to provide point estimates (with 95% confidence interval (CI)) of bacterial detection rate, inappropriate antibiotic use, and multidrug resistance rate to account for heterogeneity. The pooled bacteria detection rate was 29.1 with 95% CI (16.6-41.7). The pooled prevalence of multidrug resistant strains identified was 59.7% (95% CI: 43.5-75.9). The pooled estimate of inappropriate antibiotic use was 49.2% (95% CI: 32.2-66.2). The pooled proportion of self-antibiotic prescription was 43.3% (95% CI: 15.7-70.9). Other reasons for inappropriate antibiotic use included a wrong indication, wrong duration, improper route of administration, use of leftover antibiotics from a family member, and immature discontinuation of antibiotics.

CONCLUSION AND RECOMMENDATIONS

Inappropriate antibiotic use is a huge problem in Ethiopia, and many bacteria were resistant to commonly used antibiotics and similarly, multidrug-resistant bacterial strains are numerous. Appropriate antibiotic use should be ensured by prohibiting over-the-counter sale of antibiotics and strengthening antimicrobial stewardship.

摘要

背景

在过去几十年中,药物对健康产生了前所未有的积极影响,导致死亡率和疾病负担降低,从而提高了生活质量。抗菌耐药生物的迅速且持续传播威胁着我们成功治疗越来越多传染病的能力。在没有新一代抗生素药物研发的情况下,需要合理使用现有抗生素以确保细菌感染有效治疗的长期可及性。抗生素的不合理使用是一个持续存在的全球公共卫生问题,值得更多关注。本综述旨在评估埃塞俄比亚抗生素使用不当和抗生素耐药性的流行情况。

方法

通过在PubMed/MEDLINE和谷歌上进行电子检索,查找已发表的文献,并手动搜索相关文章的参考文献列表。首先对标题和摘要进行资格筛选。对被判定符合资格的文章全文进行审查,看其是否符合纳入标准。提取有关重要变量的数据,如样本量、研究地区、抗生素使用不当情况、细菌检出率、多重耐药模式以及更多其他变量。使用Microsoft Excel进行数据提取。使用STATA 11版本进行定量分析。

结果

电子检索共识别出193篇文章,其中33篇被判定符合资格。采用随机效应模型来提供细菌检出率、抗生素使用不当率和多重耐药率的点估计值(以及95%置信区间(CI)),以考虑异质性。汇总的细菌检出率为29.1,95% CI为(16.6 - 41.7)。所识别的多重耐药菌株的汇总流行率为59.7%(95% CI:43.5 - 75.9)。抗生素使用不当的汇总估计值为49.2%(95% CI:32.2 - 66.2)。自我开具抗生素处方的汇总比例为43.3%(95% CI:15.7 - 70.9)。抗生素使用不当的其他原因包括适应证错误、疗程错误、给药途径不当、使用家庭成员剩余的抗生素以及抗生素过早停用。

结论与建议

在埃塞俄比亚,抗生素使用不当是一个巨大问题,许多细菌对常用抗生素耐药,同样,多重耐药菌株数量众多。应通过禁止抗生素非处方销售和加强抗菌药物管理来确保合理使用抗生素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/31706c4e26bb/IJMICRO2019-2489063.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/26884f49a2d5/IJMICRO2019-2489063.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/920e57dfbaaa/IJMICRO2019-2489063.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/c373aeaf74e0/IJMICRO2019-2489063.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/88969c25cde3/IJMICRO2019-2489063.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/31706c4e26bb/IJMICRO2019-2489063.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/26884f49a2d5/IJMICRO2019-2489063.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/920e57dfbaaa/IJMICRO2019-2489063.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/c373aeaf74e0/IJMICRO2019-2489063.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/88969c25cde3/IJMICRO2019-2489063.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da3/6701335/31706c4e26bb/IJMICRO2019-2489063.005.jpg

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