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Respiratory airway resistance monitoring in mechanically ventilated patients

机译:机械通气患者的呼吸道阻力监测

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摘要

Physiological models of respiratory mechanics can be used to optimise mechanical ventilator settings to improve critically ill patient outcomes. Models are generally generated via either physical measurements or analogous behaviours that can model experimental outcomes. However, models derived solely from physical measurements are infrequently applied to clinical data.This investigation assesses the efficacy of a physically derived airway branching model (ABM) to capture clinical data. The ABM is derived via classical pressure-flow equations and branching based on known anatomy. It is compared to two well accepted lumped parameter models of the respiratory system: the linear lung model (LLM) and the Dynostatic Model (DSM).The ABM significantly underestimates the total pressure drop from the trachea to the alveoli. While the LLM and DSM both recorded peak pressure drops of 17.8 cmH2O and 10.2 cmH2O, respectively, the maximum ABM modelled pressure drop was 0.66 cmH2O. This result indicates that the anatomically accurate ABM model does not incorporate all of the airway resistances that are clinically observed in critically ill patients. In particular, it is hypothesised that the primary discrepancy is in the endotracheal tube. In contrast to the lumped parameter models, the ABM was capable of defining the pressure drop in the deep bronchial paths and thus may allow further investigation of alveoli recruitment and gas exchange at that level given realistic initial pressures at the upper airways.
机译:呼吸力学的生理模型可用于优化机械呼吸机设置,以改善危重患者的预后。通常通过物理测量或可以对实验结果建模的类似行为来生成模型。然而,仅从物理测量得出的模型很少应用于临床数据。本研究评估了物理衍生的气道分支模型(ABM)捕获临床数据的功效。 ABM是通过经典压力-流量方程式和基于已知解剖结构的分支得出的。它与呼吸系统的两个公认的集总参数模型进行了比较:线性肺部模型(LLM)和动态模型(DSM)。ABM大大低估了从气管到肺泡的总压降。尽管LLM和DSM都分别记录了17.8 cmH2O和10.2 cmH2O的峰值压降,但最大的ABM模型压降为0.66 cmH2O。该结果表明,解剖学上准确的ABM模型并未纳入在重症患者中临床观察到的所有气道阻力。特别地,假设主要差异在于气管内插管。与集总参数模型相反,ABM能够确定深层支气管路径中的压降,因此,可以根据上呼吸道的实际初始压力,进一步调查该水平的肺泡补充和气体交换。

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