Alison Wallbank, Alexander Sosa, Andrew Colson, Huda Farooqi, Elizabeth Kaye, Katharine Warner, David J Albers, Peter D Sottile, Bradford J Smith
{"title":"Dynamic driving pressure predicts ventilator-induced lung injury in mice with and without endotoxin-induced acute lung injury.","authors":"Alison Wallbank, Alexander Sosa, Andrew Colson, Huda Farooqi, Elizabeth Kaye, Katharine Warner, David J Albers, Peter D Sottile, Bradford J Smith","doi":"10.1152/ajplung.00176.2024","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":7593,"journal":{"name":"American journal of physiology. Lung cellular and molecular physiology","volume":" ","pages":"L159-L175"},"PeriodicalIF":3.6000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of physiology. Lung cellular and molecular physiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1152/ajplung.00176.2024","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PHYSIOLOGY","Score":null,"Total":0}
引用次数: 0
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 (PDDyn), mechanical power calculated by integration during inspiration or the entire respiratory cycle, and power calculated according to Gattinoni' s equation. Of these, PDDyn 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.NEW & NOTEWORTHY 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.
期刊介绍:
The American Journal of Physiology-Lung Cellular and Molecular Physiology publishes original research covering the broad scope of molecular, cellular, and integrative aspects of normal and abnormal function of cells and components of the respiratory system. Areas of interest include conducting airways, pulmonary circulation, lung endothelial and epithelial cells, the pleura, neuroendocrine and immunologic cells in the lung, neural cells involved in control of breathing, and cells of the diaphragm and thoracic muscles. The processes to be covered in the Journal include gas-exchange, metabolic control at the cellular level, intracellular signaling, gene expression, genomics, macromolecules and their turnover, cell-cell and cell-matrix interactions, cell motility, secretory mechanisms, membrane function, surfactant, matrix components, mucus and lining materials, lung defenses, macrophage function, transport of salt, water and protein, development and differentiation of the respiratory system, and response to the environment.