RESPIRATORY FUNCTION OPTIMIZATION WITH HIGH FREQ VENTIL

通常认为，低潮气量的高频通气（HFV 体积（小于解剖死腔）产生较低的肺泡 压力比传统的机械通气，从而减少 伴随的气压伤和心输出量减少的风险。 但在 初步建模研究，我们发现，这种假设并不总是 有效的. 我们提出了一系列的实验狗来测试模型 预测和进一步了解气体之间的相互作用 HFV期间的运输和肺力学。 我们将确定最佳的 HFV参数的组合，同时最大化气体 交换和最小化肺泡压力。 所讨论的参数是 频率、潮气量、气流波形和肺容量。 我们将 研究呼吸优化在某些情况下如何受到影响 模拟疾病条件。 我们还将比较应用 采用HFV的更常见模式通过胸部外振荡进行HFV 通过气管应用。 从我们对气体运输的测量来看，当地 气道转运阻力和肺机械特性，我们将 开发一个数学模型，该模型结合了气体交换和 HFV的肺力学方面，包括重要的非线性，如 气体捕集 该模型将用于生成具有临床意义的 预测如何最好地优化人类的呼吸功能 患有肺病的成人和婴儿。

It is often presumed that high frequency ventilation (HFV) with low tidal volumes (smaller than anatomic dead space) produces lower alveolar pressures than conventional mechanical ventilation, thus reducing the attendant risks of barotrauma and diminished cardiac output. However, in a preliminary modeling study, we found that this presumption is not always valid. We propose a series of experiments on dogs to test the model prediction and to further our understanding of the interaction between gas transport and lung mechanics during HFV. We will determine the optimal combination of HFV parameters that would simultaneously maximize gas exchange and minimize alveolar pressures. The parameters in question are frequency, tidal volume, airflow waveform and lung volume. We will investigate how respiratory optimization is affected under certain simulated disease conditions. We will also compare the effects of applying HFV by external chest oscillation with the more common mode of HFV application via the trachea. From our measurements of gas transport, local airway transport resistances and lung mechanical characteristics, we will develop a mathematical model that incorporates both the gas exchange and lung mechanics aspects of HFV, including important nonlinearities such as gas trapping. This model will be used to generate clinically significant predictions of how respiratory function may best be optimized in human adults and infants with pulmonary disease.