Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.
Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.
Comput Methods Programs Biomed. 2021 Sep;208:106300. doi: 10.1016/j.cmpb.2021.106300. Epub 2021 Jul 22.
Optimisation of mechanical ventilation (MV) and weaning requires insight into underlying patient breathing effort. Current identifiable models effectively describe lung mechanics, such as elastance (E) and resistance (R) at the bedside in sedated patients, but are less effective when spontaneous breathing is present. This research derives and regularises a single compartment model to identify patient-specific inspiratory effort.
Constrained second-order b-spline basis functions (knot width 0.05 s) are used to describe negative inspiratory drive (Pp, cmHO) as a function of time. Breath-breath Pp are identified with single E and R values over inspiration and expiration from n = 20 breaths for N = 22 patients on NAVA ventilation. Pp is compared to measured electrical activity of the diaphragm (Eadi) and published results.
Average per-patient root-mean-squared model fit error was (median [interquartile range, IQR]) 0.9 [0.6-1.3] cmHO, and average per-patient median Pp was -3.9 [-4.5- -3.0] cmHO, with range -7.9 - -1.9 cmHO. Per-patient E and R were 16.4 [13.6-21.8] cmHO/L and 9.2 [6.4-13.1] cmHO.s/L, respectively. Most patients showed an inspiratory volume threshold beyond which Pp started to return to baseline, and Pp at peak Eadi (end-inspiration) was often strongly correlated with peak Eadi (R=0.25-0.86). Similarly, average transpulmonary pressure was consistent breath-breath in most patients, despite differences in peak Eadi and thus peak airway pressure.
The model-based inspiratory effort aligns with electrical muscle activity and published studies showing neuro-muscular decoupling as a function of pressure and/or volume. Consistency in coupling/dynamics were patient-specific. Quantification of patient and ventilator work of breathing contributions may aid optimisation of MV modes and weaning.
优化机械通气(MV)和撤机需要深入了解患者的呼吸努力。目前可识别的模型可以有效地描述肺力学,例如在镇静患者中床边的弹性(E)和阻力(R),但在存在自主呼吸时效果较差。本研究推导并正则化了一个单室模型,以确定患者特定的吸气努力。
使用受约束的二阶 B 样条基函数(节宽 0.05 s)来描述负吸气驱动(Pp,cmHO)随时间的变化。从 22 名患者的 20 次呼吸中,使用单 E 和 R 值来识别呼吸之间的 Pp,这些患者在 NAVA 通气下进行了 n = 20 次呼吸。将 Pp 与测量的膈肌电活动(Eadi)和已发表的结果进行比较。
每位患者的平均均方根模型拟合误差为(中位数[四分位距,IQR])0.9 [0.6-1.3] cmHO,每位患者的平均 Pp 中位数为-3.9 [-4.5- -3.0] cmHO,范围为-7.9 - -1.9 cmHO。每位患者的 E 和 R 分别为 16.4 [13.6-21.8] cmHO/L 和 9.2 [6.4-13.1] cmHO.s/L。大多数患者显示出吸气量阈值,超过该阈值后 Pp 开始返回基线,并且 Pp 在峰值 Eadi(吸气末)时通常与峰值 Eadi 高度相关(R=0.25-0.86)。同样,尽管气道峰压和/或容量不同,但大多数患者的跨肺压平均在呼吸间保持一致。
基于模型的吸气努力与电肌肉活动以及显示神经肌肉解耦作为压力和/或体积函数的已发表研究一致。耦合/动力学的一致性是患者特异性的。量化患者和呼吸机呼吸做功的贡献可能有助于优化 MV 模式和撤机。