Dynamic driving pressure predicts ventilator-induced lung injury in mice with and without endotoxin-induced acute lung injury

Mechanical ventilation (MV) is a necessary lifesaving intervention for patients with acute respiratory distress syndrome (ARDS) but it can cause ventilator-induced lung injury (VILI), which contributes to the high ARDS mortality rate (∼40%). Bedside determination of optimally lung-protective ventilation settings is challenging because the evolution of VILI is not immediately reflected in clinically available, patient-level, data. The goal of this work was therefore to test ventilation waveform-derived parameters that represent the degree of ongoing VILI and can serve as targets for ventilator adjustments. VILI was generated at three different positive end-expiratory pressures in a murine inflammation-mediated (lipopolysaccharide, LPS) acute lung injury model and in initially healthy controls. LPS injury increased the expression of proinflammatory cytokines and caused widespread atelectasis, predisposing the lungs to VILI as measured in structure, mechanical function, and inflammation. Changes in lung function were used as response variables in an elastic net regression model that predicted VILI severity from tidal volume, dynamic driving pressure (PD<sub>Dyn</sub>), mechanical power calculated by integration during inspiration or the entire respiratory cycle, and power calculated according to Gattinoni' s equation. Of these, PD<sub>Dyn</sub> best predicted functional outcomes of injury using either data from the entire dataset or from 5-min time windows. The windowed data show higher predictive accuracy after an ∼1-h "run in" period and worse accuracy immediately following recruitment maneuvers. This analysis shows that low driving pressure is a computational biomarker associated with better experimental VILI outcomes and supports the use of driving pressure to guide ventilator adjustments to prevent VILI.<b>NEW & NOTEWORTHY</b> Elastic net regression analysis of ventilation waveforms recorded during mechanical ventilation of initially healthy and lung-injured mice shows that low driving pressure is a computational biomarker associated with better ventilator-induced lung injury (VILI) outcomes and supports the use of driving pressure to guide ventilator adjustments to prevent VILI.

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Publication Details

Journal
American Journal of Physiology-Lung Cellular and Molecular Physiology
Published
2024-11-27
DOI
https://doi.org/10.1152/ajplung.00176.2024
Citations
5
Primary Topic
Respiratory Support and Mechanisms
Type
article
Field-Weighted Citation Impact
2.09

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article

Dynamic driving pressure predicts ventilator-induced lung injury in mice with and without endotoxin-induced acute lung injury

Elizabeth A. Krall, Peter D. Sottile, Alexander Sosa, Alison Wallbank et al.
5 citations
American Journal of Physiology-Lung Cellular and Molecular Physiology
Respiratory Support and Mechanisms
2.09
article

Dynamic driving pressure predicts ventilator-induced lung injury in mice with and without endotoxin-induced acute lung injury

Elizabeth A. Krall, Peter D. Sottile, Alexander Sosa, Alison Wallbank, David J. Albers, Bradford J. Smith, Andrew Colson, Huda Farooqi, K Warner
article en
5 citations

Abstract

Mechanical ventilation (MV) is a necessary lifesaving intervention for patients with acute respiratory distress syndrome (ARDS) but it can cause ventilator-induced lung injury (VILI), which contributes to the high ARDS mortality rate (∼40%). Bedside determination of optimally lung-protective ventilation settings is challenging because the evolution of VILI is not immediately reflected in clinically available, patient-level, data. The goal of this work was therefore to test ventilation waveform-derived parameters that represent the degree of ongoing VILI and can serve as targets for ventilator adjustments. VILI was generated at three different positive end-expiratory pressures in a murine inflammation-mediated (lipopolysaccharide, LPS) acute lung injury model and in initially healthy controls. LPS injury increased the expression of proinflammatory cytokines and caused widespread atelectasis, predisposing the lungs to VILI as measured in structure, mechanical function, and inflammation. Changes in lung function were used as response variables in an elastic net regression model that predicted VILI severity from tidal volume, dynamic driving pressure (PD<sub>Dyn</sub>), mechanical power calculated by integration during inspiration or the entire respiratory cycle, and power calculated according to Gattinoni' s equation. Of these, PD<sub>Dyn</sub> best predicted functional outcomes of injury using either data from the entire dataset or from 5-min time windows. The windowed data show higher predictive accuracy after an ∼1-h "run in" period and worse accuracy immediately following recruitment maneuvers. This analysis shows that low driving pressure is a computational biomarker associated with better experimental VILI outcomes and supports the use of driving pressure to guide ventilator adjustments to prevent VILI.<b>NEW & NOTEWORTHY</b> Elastic net regression analysis of ventilation waveforms recorded during mechanical ventilation of initially healthy and lung-injured mice shows that low driving pressure is a computational biomarker associated with better ventilator-induced lung injury (VILI) outcomes and supports the use of driving pressure to guide ventilator adjustments to prevent VILI.

American Journal of Physiology-Lung Cellular and Molecular PhysiologyVol. 328(1)
University of Colorado Anschutz Medical Campus (US), University of Colorado Denver (US)
National Institutes of Health, National Heart, Lung, and Blood Institute, U.S. National Library of Medicine
Good health and well-being
Openalex Percentile: Top 12%
Respiratory Support and Mechanisms
2.09
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