Optimising respiratory support for early COVID-19 pneumonia: a computational modelling study

Weaver, Liam; Das, Anup; Saffaran, Sina; Yehya, Nadir; Chikhani, Marc; Scott, Timothy E.; Laffey, John G.; Hardman, Jonathan G.; Camporota, Luigi; Bates, Declan G.

Abstract

Background: Optimal respiratory support in early COVID-19 pneumonia is controversial and remains unclear. Using computational modelling, we examined whether lung injury might be exacerbated in early COVID-19 by assessing the impact of conventional oxygen therapy (COT), high-flow nasal oxygen therapy (HFNOT), continuous positive airway pressure (CPAP), and noninvasive ventilation (NIV). Methods: Using an established multi-compartmental cardiopulmonary simulator, we first modelled COT at a fixed FiO2 (0.6) with elevated respiratory effort for 30 min in 120 spontaneously breathing patients, before initiating HFNOT, CPAP, or NIV. Respiratory effort was then reduced progressively over 30-min intervals. Oxygenation, respiratory effort, and lung stress/strain were quantified. Lung-protective mechanical ventilation was also simulated in the same cohort. Results: HFNOT, CPAP, and NIV improved oxygenation compared with conventional therapy, but also initially increased total lung stress and strain. Improved oxygenation with CPAP reduced respiratory effort but lung stress/strain remained elevated for CPAP >5 cm H2O. With reduced respiratory effort, HFNOT maintained better oxygenation and reduced total lung stress, with no increase in total lung strain. Compared with 10 cm H2O PEEP, 4 cm H2O PEEP in NIV reduced total lung stress, but high total lung strain persisted even with less respiratory effort. Lung-protective mechanical ventilation improved oxygenation while minimising lung injury. Conclusions: The failure of noninvasive ventilatory support to reduce respiratory effort may exacerbate pulmonary injury in patients with early COVID-19 pneumonia. HFNOT reduces lung strain and achieves similar oxygenation to CPAP/NIV. Invasive mechanical ventilation may be less injurious than noninvasive support in patients with high respiratory effort.

Citation

Weaver, L., Das, A., Saffaran, S., Yehya, N., Chikhani, M., Scott, T. E., Laffey, J. G., Hardman, J. G., Camporota, L., & Bates, D. G. (2022). Optimising respiratory support for early COVID-19 pneumonia: a computational modelling study. British Journal of Anaesthesia, https://doi.org/10.1016/j.bja.2022.02.037

• Journal Article Type: Article
• Acceptance Date: Feb 5, 2022
• Online Publication Date: Mar 17, 2022
• Publication Date: Mar 17, 2022
• Deposit Date: Apr 20, 2022
• Publicly Available Date: Apr 20, 2022
• Journal: British Journal of Anaesthesia
• Print ISSN: 0007-0912
• Electronic ISSN: 1471-6771
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1016/j.bja.2022.02.037
• Keywords: Anesthesiology and Pain Medicine
• Public URL: https://nottingham-repository.worktribe.com/output/7783331
• Publisher URL: https://www.bjanaesthesia.org/article/S0007-0912(22)00130-1/fulltext