Differences in respiratory mechanics estimation with respect to manoeuvres and mathematical models

Abstract

The aim of mechanical ventilation (MV) is to provide sufficient breathing support for critically ill patients with respiratory failure in the intensive care unit (ICU). However, the application of inappropriate MV settings can result in ventilator induced lung injury (VILI) and exacerbate respiratory dysfunction. To prevent VILI, respiratory mechanics properties such as elastance and resistance can be estimated at the bedside to guide MV settings. Different models or methods provide different information and have unique advantages and disadvantages. In this study, the respiratory mechanics of 25 respiratory failure patients were determined using the first order model (FOM) and a viscoelastic model (VEM). The patients underwent different respiratory manoeuvres and their identified respiratory mechanics using these models are studied and compared with a standard clinical method in estimating respiratory mechanics. The results show that both models were able to capture patient-specific mechanics and responses. The FOM was able to provide higher correlation to the standard clinical method while the VEM provides a physiologically more plausible representation.

Network Data Acquisition and Monitoring System for Intensive Care Mechanical Ventilation Treatment

“…The realtime and hourly data analysis in CARENet, or similar system, can provide continuous monitoring to optimize decision making at the bedside in a clinically timely fashion. Conversely, the daily summary trend shows longer term evolution of patient condition and response, providing unique insight into patient response to the overall MV treatment approach [86]. Both outcomes provide significant input to further guide and optimize care.…”

Comparison of pressure, volume and gas washout characteristics between PCV and HFPV in healthy and formalin fixed ex vivo porcine lungs

“…CD varies from 0 to 1, CD = 1 represents a perfect fit and CD = 0 represents no fit at all. Although respiratory mechanics is a non-linear process, it is reported that the FOM is capable of correctly predicting respiratory mechanics in ICU patients (Kretschmer et al 2017). In this study, we employ FOM for the prediction of respiratory resistance and compliance of the ex vivo porcine lungs.…”