Airway resistance variation correlates with prognosis of critically ill COVID-19 patients: A computational fluid dynamics study. (September 2021)

• Record Type: Journal Article
• Authors: Pan, Shi-yu; Ding, Ming; Huang, Jing; Cai, Yan; Huang, Ying-zi
• Is Part Of: Computer methods and programs in biomedicine. Volume 208(2021)
• Publication Date: 2021-09
• Subjects: Computational fluid dynamics -- COVID-19 -- Flow resistance; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2021.106257
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: The first study to investigate the air flow changes in the airway for critically ill patients with COVID-T19 by using computational fluid dynamics (CFD) analysis. The patient-specific CFD airway analysis showed airway resistance variations that correlated with the development of the disease. CFD airway analysis could be used as a non-invasive functional evaluation for the prognosis. Abstract: Objective: To evaluate the quantitative changes of respiratory functions for critically ill COVID-19 patients with mechanical ventilation, computational fluid dynamics (CFD) analysis was performed based on patient-specific three-dimensional airway geometry. Methods: 37 cases of critically ill patients with COVID-19 admitted to the ICU of Huangshi Traditional Chinese Medicine Hospital from February 1st to March 20th, 2020 were retrospectively analyzed. 5 patients whose clinical data met the specific criteria were finally cataloged into death group (2 patients) and survival group (3 patients). The patient-specific three-dimensional airways were reconstructed from the central airways down to the 4th-5th bifurcation of the tracheobronchial tree. The volume changes of bronchi were calculated during the disease progression according to the comparison of two CT scans. Additionally, the changes of air flow resistance were analyzed using numerical simulation of CFD. Results: Pearson correlation analysis demonstrated that there was negative correlation between the change of volume (ΔV) and the change of resistance (ΔR) for all COVID-19 patients (r=-0.7025). For total airway volume, an average decrease of -11.41±15.71% was observed in death group compared to an average increase of 1.86±10.80% in survival group (p=0.0232). For air flow through airways in lower lobe, the resistance increases for death group by 10.97±77.66% and decreases for survival group by -45.49±42.04% (p=0.0246). Conclusion: The variation of flow resistance in the airway could be used as a non-invasive functional evaluation for the prognosis and outcome of critically ill patients with COVID-19. The 'virtual' pulmonary function test by integrating follow-up CT scans with patient-derived CFD analysis could be a potentially powerful way in improving the efficiency of treatment for critically ill patients with COVID-19.