Lv Yinxia, Dong Meiling, Song Haisong, Liu Jinglei, Huang Zhiwen, Ni Zhong, Wang Zhen, Jing Xiaorong, Zhou Xiaoyong, Zhou Yongfang, Kang Yan, Wang Bo
Department of Respiratory Care, West China Hospital of Sichuan University, Chengdu, 610041, China.
Shenzhen Mindray Bio-Medical Electronics Co.,Ltd., Shenzhen, 518057, China.
Crit Care. 2025 Jul 3;29(1):272. doi: 10.1186/s13054-025-05514-4.
Mechanical ventilation is essential for treating respiratory failure. However, ventilator over-assistance can lead to ventilator-induced diaphragm dysfunction (VIDD), and insufficient assistance can necessitate excessive effort, which leads to high stress and damage diaphragm function. Current methods monitoring respiratory effort face clinical implementation challenges due to invasiveness and complexity. This study introduces and validates a novel non-invasive real-time respiratory muscle pressure (N-Pmus) monitoring method.
(1) The bench study involved developing a non-invasive, real-time respiratory muscle pressure monitoring algorithm (N-Pmus) based on the equation of motion of the respiratory system and validated with efforts generated by the ASL simulator (ASL5000-Pmus) across 270 clinical scenarios. (2) A clinical validation was performed through a prospective observational study (n = 23), comparing N-Pmus with the Pmus derived from simultaneously monitored esophageal pressure (Pmus) to assess correlation and agreement. The association between N-Pmus and the established Pmus benchmarks was analyzed using linear mixed-effects models. Bias and agreement were evaluated through Bland-Altman analysis for repeated measures.
(1) The bench study demonstrated that N-Pmus correlated well with ASL5000-Pmus, with marginal R²=0.993 and conditional R²=0.997. The bias was - 0.23 cmH₂O, with limits of agreement ranging from - 1.51 to 1.04 cmH₂O. (2) The clinical validation revealed strong N-Pmus/Pmus agreement with marginal R²=0.97 and conditional R²=0.971. The bias was - 0.2 cmH₂O, with limits of agreement ranging from - 2.22 to 1.83 cmH₂O.
Retrospectively registered with https://www.chictr.org.cn/ .
ChiCTR2300076940, registered 24 October 2023.
机械通气对于治疗呼吸衰竭至关重要。然而，通气过度辅助会导致呼吸机诱发的膈肌功能障碍（VIDD），而辅助不足则会导致用力过度，进而导致高压力并损害膈肌功能。目前监测呼吸用力的方法由于具有侵入性和复杂性，面临临床应用挑战。本研究介绍并验证了一种新型的非侵入性实时呼吸肌压力（N-Pmus）监测方法。
（1）实验台研究包括基于呼吸系统运动方程开发一种非侵入性实时呼吸肌压力监测算法（N-Pmus），并在270种临床场景下用ASL模拟器（ASL5000-Pmus）产生的用力进行验证。（2）通过一项前瞻性观察性研究（n = 23）进行临床验证，将N-Pmus与同时监测的食管压力得出的Pmus进行比较，以评估相关性和一致性。使用线性混合效应模型分析N-Pmus与既定Pmus基准之间的关联。通过Bland-Altman分析重复测量来评估偏差和一致性。
（1）实验台研究表明，N-Pmus与ASL5000-Pmus相关性良好，边际R² = 0.993，条件R² = 0.997。偏差为-0.23 cmH₂O，一致性界限为-1.51至1.04 cmH₂O。（2）临床验证显示N-Pmus/Pmus具有很强的一致性，边际R² = 0.97，条件R² = 0.971。偏差为-0.2 cmH₂O，一致性界限为-2.22至1.83 cmH₂O。
在https://www.chictr.org.cn/进行回顾性注册。
ChiCTR2300076940，于2023年10月24日注册。
