Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure

Author:

Lin Tiantian1,Lin Qiaoyan2,Feng Yuying3,Dong Lingchu4ORCID

Affiliation:

1. Respiratory Intensive Care Unit, Yantai Yuhuangding Hospital, Yantai, 264000 Shandong, China

2. Cardiac Intensive Care Unit, Yantai Yuhuangding Hospital, Yantai, 264000 Shandong, China

3. Pain Management Department, Yidu Central Hospital of Weifang, Weifang, 262500 Shandong, China

4. Medical Ward, Yantai Yuhuangding Hospital Laishan Branch, Yantai, 264000 Shandong, China

Abstract

Heart failure is the final stage of the development of heart disease, with a high mortality and disability rate. It poses a serious threat to human health and brings tremendous pressure to human society. Preventing respiratory infections in patients with heart failure is also the first priority of care. This article is aimed at studying the nursing analysis of respiratory tract care based on big data exchanges to prevent respiratory tract infections in patients with heart failure. This article uses benchmark and sample collection. Studies have shown that for Pseudomonas aeruginosa, its resistance to ampicillin, amoxicillin/clavulanic acid, cefazolin, cefuroxime, ceftriaxone, cefotaxime, and cefoxitin has reached more than 80%. It is also suitable for piperacillin, ticarcillin/clavulanic acid, piperacillin/tazobactam, cefepime, aztreonam, gentamicin, tobramycin, ciprofloxacin, and levofloxacin. The resistance rate of stars is within 10%-30%. These antibiotics are effective and can be used for clinical treatment. The drug resistance rates of ceftazidime, imipenem, meropenem, and amikacin were all lower than 10%, and the drug resistance rates of ceftazidime and imipenem were much lower than those reported in the 2016 literature. These antibiotics have become the most effective drugs for the treatment of Pseudomonas aeruginosa infections. Basically, good communication of respiratory care data is realized, thereby preventing respiratory care analysis of patients with heart failure.

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Retracted: Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure;BioMed Research International;2023-07-12

2. Application of Machine Learning for Heart Failure Prediction;2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD);2023-05-26

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3