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Quantifying patient spontaneous breathing effort using model-based methods

机译:使用基于模型的方法量化患者自发呼吸努力

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Background: Spontaneous breathing (SB) effort is common in invasively ventilated patients, as they recover or at low sedation levels. SB effort makes estimation of patient-specific lung mechanics difficult as it introduces unknown inputs. Currently, there is no proven, non-invasive method to quantify SB effort. This study develops noninvasive model-based metrics for SB. Methods: Lung mechanics are identified using a proven model to identify time-varying elastance over inspiration using retrospective data from 22 patients on neutrally adjusted ventilatory assist (NAVA) ventilation. Two methods are explored to quantify negative elastance values associated with breathing effort: a zero-crossing and a trapezoidal method. Area under the resulting positive and negative portions of the time-varying elastance curve is used to quantify SB. Results: The median [interquartile range (IQR)] of AUC quantification of SB for the zero crossing method was -3.29 [-4.80 to -2.50] cmH2O/l, and -1.90 [-2.36 to -1.66] cmH2O/l for the trapezoidal method. AUC values between the two methods were highly correlated, indicating consistency of both model-based methods to quantify SB. Conclusion: Two model-based methods for SB quantification provide consistent metrics for SB. These methods provide computationally simple and cost effective methods to estimate SB effort, which may have clinical value in assessing patient-ventilator synchrony, choice of ventilation mode, or need for weaning.
机译:背景:自发呼吸(SB)努力在侵略性通风患者中常见,因为它们恢复或低镇静水平。 SB努力使患者特异性肺部力学估计难以推出未知的输入。目前,没有经过验证的,非侵入性的方法来量化SB努力。本研究开发了基于非侵入性模型的SB度量。方法:使用经过验证的模型识别肺部力学,以使用来自22名患者在中性调整的通风辅助(Nava)通风中的回顾性数据来识别超变的弹性。探索了两种方法以量化与呼吸努力相关的负弹性值:零交叉和梯形方法。由此产生的时变弹性曲线的正面和负部分下的区域用于量化Sb。结果:零交叉方法SB的AUC定量的中值[四分位数(IQR)定量定量为-3.29 [-4.80至-2.50] CMH2O / L, - 1.90 [-2.36至-1.66] CMH2O / L.梯形方法。两种方法之间的AUC值是高度相关的,表明基于模型的方法的一致性来量化SB。结论:用于SB量化的两种基于模型的方法为SB提供一致的度量。这些方法提供了计算简单且具有成本效益的方法来估计SB努力,这可能具有评估患者通风机同步,通风模式选择或需要断奶的临床价值。

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