Evaluation of Emerging Antimicrobials Resistance in Nosocomial Infections Caused by E. coli: The Comparison Results of Observed Cases and Compartmental Model.

Q3 Immunology and Microbiology
Interdisciplinary Perspectives on Infectious Diseases Pub Date : 2025-01-16 eCollection Date: 2025-01-01 DOI:10.1155/ipid/3134775
Babak Eshrati, Elaheh Karimzadeh-Soureshjani, Mahshid Nasehi, Leila Janani, Hamid Reza Baradaran, Saeid Bitaraf, Pouria Ahmadi Simab, Sara Mobarak, Sasan Ghorbani Kalkhajeh, Mohammad Kogani
{"title":"Evaluation of Emerging Antimicrobials Resistance in Nosocomial Infections Caused by <i>E. coli</i>: The Comparison Results of Observed Cases and Compartmental Model.","authors":"Babak Eshrati, Elaheh Karimzadeh-Soureshjani, Mahshid Nasehi, Leila Janani, Hamid Reza Baradaran, Saeid Bitaraf, Pouria Ahmadi Simab, Sara Mobarak, Sasan Ghorbani Kalkhajeh, Mohammad Kogani","doi":"10.1155/ipid/3134775","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> In recent years, the global rise of antibiotic-resistant <i>Escherichia coli</i> (<i>E. coli</i>) has become a significant threat to public health. This study aimed to identify and track outbreaks of antibiotic resistance, specifically among the antibiotics used to treat nosocomial <i>E. coli</i> infections. <b>Materials and Methods:</b> This hospital-based study utilized data from a nosocomial infection surveillance system to investigate reported cases of antibiotic resistance. The study analyzed the results of 12,954 antibiogram tests conducted across 57 hospitals in 31 provinces of Iran. The data was divided into two periods: the first and second halves of 2017. Before developing a predictive model for resistant <i>E. coli</i> cases, the model's validity was tested using the first half of the year's data. The predicted cases were then compared to the actual observed cases in 2017, with a statistically significant difference indicating an outbreak. <b>Findings:</b> The study found that, in 2017, hospitals in Iran experienced an outbreak of <i>E. coli</i> resistant to ampicillin and ceftazidime. This resistance was more prevalent than expected, highlighting the emergence of these drugs as major contributors to nosocomial <i>E. coli</i> infections. <b>Conclusion:</b> This study demonstrated the utility of the compartmental model in forecasting outbreaks of antibiotic-resistant <i>E. coli</i>. It provides a framework for investigating similar outbreaks in the future, using diverse data sources and methodologies.</p>","PeriodicalId":39128,"journal":{"name":"Interdisciplinary Perspectives on Infectious Diseases","volume":"2025 ","pages":"3134775"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11756951/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interdisciplinary Perspectives on Infectious Diseases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/ipid/3134775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"Immunology and Microbiology","Score":null,"Total":0}
引用次数: 0

Abstract

Background: In recent years, the global rise of antibiotic-resistant Escherichia coli (E. coli) has become a significant threat to public health. This study aimed to identify and track outbreaks of antibiotic resistance, specifically among the antibiotics used to treat nosocomial E. coli infections. Materials and Methods: This hospital-based study utilized data from a nosocomial infection surveillance system to investigate reported cases of antibiotic resistance. The study analyzed the results of 12,954 antibiogram tests conducted across 57 hospitals in 31 provinces of Iran. The data was divided into two periods: the first and second halves of 2017. Before developing a predictive model for resistant E. coli cases, the model's validity was tested using the first half of the year's data. The predicted cases were then compared to the actual observed cases in 2017, with a statistically significant difference indicating an outbreak. Findings: The study found that, in 2017, hospitals in Iran experienced an outbreak of E. coli resistant to ampicillin and ceftazidime. This resistance was more prevalent than expected, highlighting the emergence of these drugs as major contributors to nosocomial E. coli infections. Conclusion: This study demonstrated the utility of the compartmental model in forecasting outbreaks of antibiotic-resistant E. coli. It provides a framework for investigating similar outbreaks in the future, using diverse data sources and methodologies.

评价大肠杆菌引起的医院感染新出现的抗生素耐药性:观察病例与室室模型的比较结果。
背景:近年来,抗生素耐药大肠杆菌(E. coli)在全球范围内的兴起已成为对公共卫生的重大威胁。本研究旨在识别和追踪抗生素耐药性的爆发,特别是用于治疗院内大肠杆菌感染的抗生素。材料和方法:这项以医院为基础的研究利用了医院感染监测系统的数据来调查报告的抗生素耐药性病例。该研究分析了在伊朗31个省的57家医院进行的12954次抗生素检测结果。该数据分为两个时期:2017年上半年和下半年。在开发耐药大肠杆菌病例的预测模型之前,使用今年上半年的数据测试了该模型的有效性。然后将预测的病例与2017年实际观察到的病例进行比较,差异具有统计学意义,表明疫情爆发。研究结果:该研究发现,2017年,伊朗医院爆发了对氨苄西林和头孢他啶耐药的大肠杆菌。这种耐药性比预期的更为普遍,凸显了这些药物作为院内大肠杆菌感染的主要因素的出现。结论:本研究证明了区室模型在预测耐药大肠杆菌暴发中的实用性。它提供了一个框架,可以使用不同的数据源和方法调查未来类似的疫情。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.10
自引率
0.00%
发文量
51
审稿时长
18 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信