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.
| Original language | English |
|---|---|
| Pages (from-to) | 1052-1058 |
| Number of pages | 7 |
| Journal | British Journal of Anaesthesia |
| Volume | 128 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Keywords
- acute respiratory failure
- computational modelling
- COVID-19
- mechanical ventilation
- noninvasive respiratory support
- patient self-inflicted lung injury
Fingerprint
Dive into the research topics of 'Optimising respiratory support for early COVID-19 pneumonia: a computational modelling study'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver