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PMID: 37413823 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

Computational fluid dynamics can detect changes in airway resistance for patients after COVID-19 infection.

Journal of biomechanics ·Vol. 157 ·2023-00-00 ·页码 111713

Qiu Y, Jiang Z, Sun H, Xia Q, Liu X, Lei J, Li K

Abstract

Infection with COVID-19 can cause severe complication in the respiratory system, which may be related to increased respiratory resistance. Computational fluid dynamics(CFD) was used in this study to calculate the airway resistance based on the airway anatomy and a common air flowrate. The correlation between airway resistance and COVID-19 prognosis was then investigated. A total of 23 COVID-19 patients with 54 CT scans were grouped into the good prognosis and bad prognosis group based on whether the CT scan shows significant decrease in the pneumonia volume after one week treatment and retrospectively analyzed. A baseline group of 8 healthy people with the same age and gender ratio is enrolled for comparison. Results show that the airway resistance at admission is significantly higher for COVID-19 patients with poor prognosis than those with good prognosis and the baseline(0.063 ± 0.055 vs 0.029 ± 0.011 vs 0.017 ± 0.006 Pa/(ml/s),p = 0.01). In the left superior lobe (r = 0.3974,p = 0.01),left inferior lobe (r = 0.4843,p < 0.01), the right inferior lobe (r = 0.5298,p < 0.0001), the airway resistance was significantly correlated with the degree of pneumonia infection. It is concluded that for COVID-19 patients', airway resistance at admission is closely associated with their prognosis, and has the clinical potential to be used as an index for patients' diagnosis.

Keywords
Airway resistance Biomechanics COVID-19 Computational fluid dynamics(CFD) Pulmonary function
MeSH 主题词
Humans Airway Resistance Retrospective Studies Hydrodynamics COVID-19 Lung/diagnostic imaging
作者与单位
共 7 位作者,点击展开单位 / ORCID
Qiu Yue
Department of Pulmonary and critical care medicine and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Med-X Center for Informatics Sichuan University, Chengdu, Sichuan, China; West China Hospital- SenseTime Joint Lab, Chengdu, Sichuan, China.
Jiang Zekun
Department of Pulmonary and critical care medicine and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Med-X Center for Informatics Sichuan University, Chengdu, Sichuan, China; West China Hospital- SenseTime Joint Lab, Chengdu, Sichuan, China.
Sun Hui
SenseTime Research, Beijing, China; West China Hospital- SenseTime Joint Lab, Chengdu, Sichuan, China.
Xia Qing
SenseTime Research, Beijing, China; West China Hospital- SenseTime Joint Lab, Chengdu, Sichuan, China.
Liu Xinglong
SenseTime Research, Beijing, China.
Lei Jianguo
Med-X Center for Informatics Sichuan University, Chengdu, Sichuan, China.
Li Kang
Department of Pulmonary and critical care medicine and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Med-X Center for Informatics Sichuan University, Chengdu, Sichuan, China; West China Hospital- SenseTime Joint Lab, Chengdu, Sichuan, China. Electronic address: [email protected].
Article Info
Journal
Journal of biomechanics
Abbr.
J Biomech
ISSN
1873-2380
Corresponding email
Published
2023-00-00
电子出版
2023-00-01
页码
111713
Language
English
Country/Region
United States
NLM ID
0157375
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