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Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques

Cough is a protective respiratory reflex used to clear respiratory airway mucus. For patients with cough weakness, such as chronic obstructive pulmonary disease, neuromuscular weakness disease and other respiratory diseases, assisted coughing techniques are essential to help them clear mucus. In thi...

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Autores principales: Ren, Shuai, Li, Wei, Wang, Lin, Shi, Yan, Cai, Maolin, Hao, Liming, Luo, Zihao, Niu, Jinglong, Xu, Weiqing, Luo, Zujin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005022/
https://www.ncbi.nlm.nih.gov/pubmed/32029825
http://dx.doi.org/10.1038/s41598-020-58922-7
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author Ren, Shuai
Li, Wei
Wang, Lin
Shi, Yan
Cai, Maolin
Hao, Liming
Luo, Zihao
Niu, Jinglong
Xu, Weiqing
Luo, Zujin
author_facet Ren, Shuai
Li, Wei
Wang, Lin
Shi, Yan
Cai, Maolin
Hao, Liming
Luo, Zihao
Niu, Jinglong
Xu, Weiqing
Luo, Zujin
author_sort Ren, Shuai
collection PubMed
description Cough is a protective respiratory reflex used to clear respiratory airway mucus. For patients with cough weakness, such as chronic obstructive pulmonary disease, neuromuscular weakness disease and other respiratory diseases, assisted coughing techniques are essential to help them clear mucus. In this study, the Eulerian wall film model was applied to simulate the coughing clearance process through a computational fluid dynamics methodology. Airway generation 0 to generation 2 based on realistic geometry is considered in this study. To quantify cough effectiveness, cough efficiency was calculated. Moreover, simulations of four different coughing techniques applied for chronic obstructive pulmonary disease and neuromuscular weakness disease were conducted. The influences of mucus film thickness and mucus viscosity on cough efficiency were analyzed. From the simulation results, we found that with increasing mucus film thickness and decreasing mucus viscosity, cough efficiency improved accordingly. Assisted coughing technologies have little influence on the mucus clearance of chronic obstructive pulmonary disease models. Finally, it was observed that the cough efficiency of the mechanical insufflation-exsufflation technique (MIE) is more than 40 times the value of an unassisted coughing technique, which indicates that the MIE technology has a great effect on airway mucus clearance for neuromuscular weakness disease models.
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spelling pubmed-70050222020-02-14 Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques Ren, Shuai Li, Wei Wang, Lin Shi, Yan Cai, Maolin Hao, Liming Luo, Zihao Niu, Jinglong Xu, Weiqing Luo, Zujin Sci Rep Article Cough is a protective respiratory reflex used to clear respiratory airway mucus. For patients with cough weakness, such as chronic obstructive pulmonary disease, neuromuscular weakness disease and other respiratory diseases, assisted coughing techniques are essential to help them clear mucus. In this study, the Eulerian wall film model was applied to simulate the coughing clearance process through a computational fluid dynamics methodology. Airway generation 0 to generation 2 based on realistic geometry is considered in this study. To quantify cough effectiveness, cough efficiency was calculated. Moreover, simulations of four different coughing techniques applied for chronic obstructive pulmonary disease and neuromuscular weakness disease were conducted. The influences of mucus film thickness and mucus viscosity on cough efficiency were analyzed. From the simulation results, we found that with increasing mucus film thickness and decreasing mucus viscosity, cough efficiency improved accordingly. Assisted coughing technologies have little influence on the mucus clearance of chronic obstructive pulmonary disease models. Finally, it was observed that the cough efficiency of the mechanical insufflation-exsufflation technique (MIE) is more than 40 times the value of an unassisted coughing technique, which indicates that the MIE technology has a great effect on airway mucus clearance for neuromuscular weakness disease models. Nature Publishing Group UK 2020-02-06 /pmc/articles/PMC7005022/ /pubmed/32029825 http://dx.doi.org/10.1038/s41598-020-58922-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ren, Shuai
Li, Wei
Wang, Lin
Shi, Yan
Cai, Maolin
Hao, Liming
Luo, Zihao
Niu, Jinglong
Xu, Weiqing
Luo, Zujin
Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques
title Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques
title_full Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques
title_fullStr Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques
title_full_unstemmed Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques
title_short Numerical Analysis of Airway Mucus Clearance Effectiveness Using Assisted Coughing Techniques
title_sort numerical analysis of airway mucus clearance effectiveness using assisted coughing techniques
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005022/
https://www.ncbi.nlm.nih.gov/pubmed/32029825
http://dx.doi.org/10.1038/s41598-020-58922-7
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