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

急性呼吸窘迫综合征 机械通风 医学 促炎细胞因子 肺不张 通风(建筑) 潮气量 炎症 呼吸系统 麻醉 内科学 机械工程 工程类
作者
Alison Wallbank,Alexander Sosa,Andrew Colson,Huda Farooqi,Elizabeth A. Krall,K Warner,David J. Albers,Peter D. Sottile,Bradford J. Smith
出处
期刊:American Journal of Physiology-lung Cellular and Molecular Physiology [American Physical Society]
标识
DOI:10.1152/ajplung.00176.2024
摘要

Mechanical ventilation 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 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 Dyn ), mechanical power calculated by integration during inspiration or the entire respiratory cycle, and power calculated according to Gattinoni’ s equation. Of these, PD Dyn best predicted functional outcomes of injury using either data from the entire dataset or from 5-minute time windows. The windowed data shows higher predictive accuracy after a ≈1-hour ‘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.

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