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

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 c...

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Autores principales: Lin, Tiantian, Lin, Qiaoyan, Feng, Yuying, Dong, Lingchu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458378/
https://www.ncbi.nlm.nih.gov/pubmed/36093392
http://dx.doi.org/10.1155/2022/4310841
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author Lin, Tiantian
Lin, Qiaoyan
Feng, Yuying
Dong, Lingchu
author_facet Lin, Tiantian
Lin, Qiaoyan
Feng, Yuying
Dong, Lingchu
author_sort Lin, Tiantian
collection PubMed
description 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.
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spelling pubmed-94583782022-09-09 Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure Lin, Tiantian Lin, Qiaoyan Feng, Yuying Dong, Lingchu Biomed Res Int Research Article 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. Hindawi 2022-09-01 /pmc/articles/PMC9458378/ /pubmed/36093392 http://dx.doi.org/10.1155/2022/4310841 Text en Copyright © 2022 Tiantian Lin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lin, Tiantian
Lin, Qiaoyan
Feng, Yuying
Dong, Lingchu
Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure
title Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure
title_full Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure
title_fullStr Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure
title_full_unstemmed Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure
title_short Respiratory Care of Big Data Communication to Prevent Respiratory Tract Infection Nursing Analysis of Patients with Heart Failure
title_sort respiratory care of big data communication to prevent respiratory tract infection nursing analysis of patients with heart failure
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458378/
https://www.ncbi.nlm.nih.gov/pubmed/36093392
http://dx.doi.org/10.1155/2022/4310841
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