van Diepen A, Bakkes T H G F, De Bie A J R, Turco S, Bouwman R A, Woerlee P H, Mischi M
Department of Electrical Engineering, Technische Universiteit Eindhoven, De Zaale, Eindhoven, 5612AZ, Noord-Brabant, the Netherlands.
Catharina Hospital, Michelangelolaan 2, Eindhoven, 5623 EJ, Noord-Brabant, the Netherlands.
Heliyon. 2023 Feb 10;9(2):e13610. doi: 10.1016/j.heliyon.2023.e13610. eCollection 2023 Feb.
There is a clinical need for monitoring inspiratory effort to prevent lung- and diaphragm injury in patients who receive supportive mechanical ventilation in an Intensive Care Unit. Different pressure-based techniques are available to estimate this inspiratory effort at the bedside, but the accuracy of their effort estimation is uncertain since they are all based on a simplified linear model of the respiratory system, which omits gas compressibility of air, and the viscoelasticity and nonlinearities of the respiratory system. The aim of this in-silico study was to provide an overview of the pressure-based estimation techniques and to evaluate their accuracy using a more sophisticated model of the respiratory system and ventilator. The influence of the following parameters on the accuracy of the pressure-based estimation techniques was evaluated using the in-silico model: 1) the patient's respiratory mechanics 2) PEEP and the inspiratory pressure of the ventilator 3) gas compressibility of air 4) viscoelasticity of the respiratory system 5) the strength of the inspiratory effort. The best-performing technique in terms of accuracy was the whole breath occlusion. The average error and maximum error were the lowest for all patient archetypes. We found that the error was related to the expansion of gas in the breathing set and lungs and respiratory compliance. However, concerns exist that other factors not included in the model, such as a changed muscle-force relation during an occlusion, might influence the true accuracy. The estimation techniques based on the esophageal pressure showed an error related to the viscoelastic element in the model which leads to a higher error than the occlusion. The error of the esophageal pressure-based techniques is therefore highly dependent on the pathology of the patient and the settings of the ventilator and might change over time while a patient recovers or becomes more ill.
在重症监护病房接受支持性机械通气的患者中，临床上需要监测吸气努力以预防肺和膈肌损伤。有多种基于压力的技术可在床边估算这种吸气努力，但由于它们都基于呼吸系统的简化线性模型，该模型忽略了空气的气体可压缩性以及呼吸系统的粘弹性和非线性，因此其努力估算的准确性尚不确定。这项计算机模拟研究的目的是概述基于压力的估算技术，并使用更复杂的呼吸系统和呼吸机模型评估其准确性。使用计算机模拟模型评估了以下参数对基于压力的估算技术准确性的影响：1）患者的呼吸力学；2）呼气末正压（PEEP）和呼吸机的吸气压力；3）空气的气体可压缩性；4）呼吸系统的粘弹性；5）吸气努力的强度。在准确性方面表现最佳的技术是全呼吸阻断法。对于所有患者原型，平均误差和最大误差都是最低的。我们发现误差与呼吸回路和肺部中气体的膨胀以及呼吸顺应性有关。然而，有人担心模型中未包括的其他因素，例如阻断期间肌肉力量关系的变化，可能会影响真正的准确性。基于食管压力的估算技术显示出与模型中的粘弹性元件相关的误差，这导致比阻断法更高的误差。因此，基于食管压力的技术的误差高度依赖于患者的病理状况和呼吸机的设置，并且可能会随着患者康复或病情加重而随时间变化。
