High risk of patient self-inflicted lung injury in COVID-19 with frequently encountered spontaneous breathing patterns: a computational modelling study

  1. Liam Weaver
  2. Anup Das
  3. Sina Saffaran
  4. Nadir Yehya
  5. Timothy E. Scott
  6. Marc Chikhani
  7. John G. Laffey
  8. Jonathan G. Hardman
  9. Luigi Camporota
  10. Declan G. Bates

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Abstract

Background

There is on-going controversy regarding the potential for increased respiratory effort to generate patient self-inflicted lung injury (P-SILI) in spontaneously breathing patients with COVID-19 acute hypoxaemic respiratory failure. However, direct clinical evidence linking increased inspiratory effort to lung injury is scarce. We adapted a computational simulator of cardiopulmonary pathophysiology to quantify the mechanical forces that could lead to P-SILI at different levels of respiratory effort. In accordance with recent data, the simulator parameters were manually adjusted to generate a population of 10 patients that recapitulate clinical features exhibited by certain COVID-19 patients, i.e., severe hypoxaemia combined with relatively well-preserved lung mechanics, being treated with supplemental oxygen.

Results

Simulations were conducted at tidal volumes (VT) and respiratory rates (RR) of 7 ml/kg and 14 breaths/min (representing normal respiratory effort) and at VT/RR of 7/20, 7/30, 10/14, 10/20 and 10/30 ml/kg / breaths/min. While oxygenation improved with higher respiratory efforts, significant increases in multiple indicators of the potential for lung injury were observed at all higher VT/RR combinations tested. Pleural pressure swing increased from 12.0 ± 0.3 cmH 2 O at baseline to 33.8 ± 0.4 cmH 2 O at VT/RR of 7 ml/kg/30 breaths/min and to 46.2 ± 0.5 cmH 2 O at 10 ml/kg/30 breaths/min. Transpulmonary pressure swing increased from 4.7 ± 0.1 cmH 2 O at baseline to 17.9 ± 0.3 cmH 2 O at VT/RR of 7 ml/kg/30 breaths/min and to 24.2 ± 0.3 cmH 2 O at 10 ml/kg/30 breaths/min. Total lung strain increased from 0.29 ± 0.006 at baseline to 0.65 ± 0.016 at 10 ml/kg/30 breaths/min. Mechanical power increased from 1.6 ± 0.1 J/min at baseline to 12.9 ± 0.2 J/min at VT/RR of 7 ml/kg/30 breaths/min, and to 24.9 ± 0.3 J/min at 10 ml/kg/30 breaths/min. Driving pressure increased from 7.7 ± 0.2 cmH 2 O at baseline to 19.6 ± 0.2 cmH 2 O at VT/RR of 7 ml/kg/30 breaths/min, and to 26.9 ± 0.3 cmH 2 O at 10 ml/kg/30 breaths/min.

Conclusions

Our results suggest that the forces generated by increased inspiratory effort commonly seen in COVID-19 acute hypoxaemic respiratory failure are comparable with those that have been associated with ventilator-induced lung injury during mechanical ventilation. Respiratory efforts in these patients should be carefully monitored and controlled to minimise the risk of lung injury.

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  1. Version published to 10.1186/s13613-021-00904-7
  2. Version published to 10.1101/2021.03.17.21253788v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.03.17.21253788: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All model simulations were run for 30 minutes, with the reported data averaged over the final 1 minute, and conducted using Matlab version R2019b.v9 (MathWorks Inc.,
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has some limitations, principally that the results are based on computational modeling of COVID-19 pathophysiology, rather than data from patients with COVID-19. Investigating the issues raised here in clinical trials is likely to prove challenging both from an ethical and practical point of view, however, and suitable animal models of COVID-19 pathophysiology to study these questions are yet to emerge (52). In these circumstances, we hope that insights from detailed computational models that recapitulate patient breathing patterns and lung mechanics can provide useful evidence with which to inform current debate.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  4. Version published to 10.1101/2021.03.17.21253788v1 on medRxiv