Expiratory Pause Maneuver to Assess Inspiratory Muscle Pressure During Assisted Mechanical Ventilation: A Bench Study

State of the art: Monitoring of the respiratory system during veno-venous extracorporeal membrane oxygenation

Monitoring the patient receiving veno-venous extracorporeal membrane oxygenation (VV ECMO) is challenging due to the complex physiological interplay between native and membrane lung. Understanding these interactions is essential to understand the utility and limitations of different approaches to respiratory monitoring during ECMO. We present a summary of the underlying physiology of native and membrane lung gas exchange and describe different tools for titrating and monitoring gas exchange during ECMO. However, the most important role of VV ECMO in severe respiratory failure is as a means of avoiding further ergotrauma. Although optimal respiratory management during ECMO has not been defined, over the last decade there have been advances in multimodal respiratory assessment which have the potential to guide care. We describe a combination of imaging, ventilator-derived or invasive lung mechanic assessments as a means to individualise management during ECMO.

Evaluation of the accuracy of established patient inspiratory effort estimation methods during mechanical support ventilation

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.

The Effect of Inspiratory Effort on Circuit Compensation for Volume-Targeted Modes

BACKGROUND

Critical-care ventilators provide patient circuit compensation (CC) to counteract the loss of volume due to patient circuit compliance. No studies show the effect of inspiratory efforts (indicating maximal value of the muscle pressure waveforms [P_max]) on CC function. The goal of this study was to determine how P_max affects volume delivery with or without CC for both volume control continuous mandatory ventilation with set-point targeting scheme (VC-CMVs) and pressure control continuous mandatory ventilation with adaptive targeting scheme (PC-CMVa) modes on the Servo-u ventilator.

METHODS

A breathing simulator was programmed to represent an adult with moderate ARDS with different P_max. It was connected to a ventilator set to VC-CMVs or PC-CMVa. The change in tidal volume (ΔV_T) was defined as the difference between V_T with CC on versus off. V_T error was defined as the difference between the simulator displayed V_T and the set V_T with CC on versus off.

RESULTS

For both VC-CMVs and PC-CMVa modes, ΔV_T decreased as P_max increased. The V_T error decreased as P_max increas-ed for VC-CMVs. In contrast, V_T error increased on PC-CMVa mode as P_max increased and peaked 39.0% for P_max = 15 cm H₂O. For both modes, the difference in V_T errors for CC on versus CC off decreased as P_max increased.

CONCLUSIONS

CC corrected the delivered V_T for volume lost due to compression in the patient circuit as expected. This compensation volume decreases as airway pressure drops due to patient P_max.