Background

: 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.

Methods

: Constrained second-order b-spline basis functions (knot width 0.05 seconds) are used to describe negative inspiratory drive (Pp, cmH₂O) 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.

Results

: Average per-patient root-mean-squared model fit error was (median [interquartile range, IQR]) 0.9 [0.6–1.3] cmH₂O, and average per-patient median Pp was -3.9 [-4.5– -3.0] cmH₂O, with range -7.9 – -1.9 cmH₂O. Per-patient E and R were 16.4 [13.6–21.8] cmH₂O/L and 9.2 [6.4–13.1] cmH₂O.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 (R²=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.

Conclusions

: 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.

中文翻译：

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接受有创 NAVA 机械通气患者吸气负压的基于模型的估计

背景

：机械通气 (MV) 和撤机的优化需要深入了解潜在的患者呼吸努力。当前可识别的模型有效地描述了肺力学，例如镇静患者在床边的弹性 (E) 和阻力 (R)，但在存在自主呼吸时效果较差。这项研究推导出并规范了一个单一的隔室模型，以识别患者特定的吸气努力。

方法

：受约束的二阶 b 样条基函数（结宽度 0.05 秒）用于将负吸气驱动 (Pp, cmH ₂ O) 描述为时间的函数。对于 N=22 位 NAVA 通气患者，呼吸-呼吸 Pp 用单个 E 和 R 值在吸气和呼气期间从 n=20 次呼吸确定。Pp 与测量的隔膜电活动 (Eadi) 和公布的结果进行比较。

结果

：平均每名患者均方根模型拟合误差为（中位数 [四分位距，IQR]）0.9 [0.6–1.3] cmH ₂ O，平均每名患者中位数 Pp 为 -3.9 [-4.5– -3.0] cmH ₂ O，范围为 -7.9 – -1.9 cmH ₂ O。每位患者的 E 和 R 分别为 16.4 [13.6–21.8] cmH ₂ O/L 和 9.2 [6.4–13.1] cmH ₂ O.s/L。大多数患者表现出吸气量阈值，超过该阈值 Pp 开始返回基线，并且 Eadi 峰值（吸气末）的 Pp 通常与 Eadi 峰值密切相关（R ² =0.25-0.86）。同样，尽管 Eadi 峰值和气道压力峰值存在差异，但大多数患者的平均跨肺压与呼吸一致。

结论

：基于模型的吸气努力与肌肉电活动和已发表的研究一致，显示神经肌肉解耦是压力和/或容量的函数。耦合/动力学的一致性是特定于患者的。患者和呼吸机呼吸功的量化可能有助于优化 MV 模式和撤机。