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Open Access Technical advance

Visualisation of time-varying respiratory system elastance in experimental ARDS animal models

Erwin J van Drunen1, Yeong Shiong Chiew1, Christopher Pretty1, Geoffrey M Shaw3, Bernard Lambermont4, Nathalie Janssen4, J Geoffrey Chase1 and Thomas Desaive2*

Author Affiliations

1 University of Canterbury, Christchurch 8041, New Zealand

2 University of Liège, Liège, Belgium

3 Christchurch Hospital, Christchurch 8011, New Zealand

4 University Hospital of Liège, Liège, Belgium

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BMC Pulmonary Medicine 2014, 14:33  doi:10.1186/1471-2466-14-33

Published: 2 March 2014

Abstract

Background

Patients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics. Model-based estimation of respiratory mechanics characterising patient-specific condition and response to treatment may be used to guide mechanical ventilation (MV). This study presents a model-based approach to monitor time-varying patient-ventilator interaction to guide positive end expiratory pressure (PEEP) selection.

Methods

The single compartment lung model was extended to monitor dynamic time-varying respiratory system elastance, Edrs, within each breathing cycle. Two separate animal models were considered, each consisting of three fully sedated pure pietrain piglets (oleic acid ARDS and lavage ARDS). A staircase recruitment manoeuvre was performed on all six subjects after ARDS was induced. The Edrs was mapped across each breathing cycle for each subject.

Results

Six time-varying, breath-specific Edrs maps were generated, one for each subject. Each Edrs map shows the subject-specific response to mechanical ventilation (MV), indicating the need for a model-based approach to guide MV. This method of visualisation provides high resolution insight into the time-varying respiratory mechanics to aid clinical decision making. Using the Edrs maps, minimal time-varying elastance was identified, which can be used to select optimal PEEP.

Conclusions

Real-time continuous monitoring of in-breath mechanics provides further insight into lung physiology. Therefore, there is potential for this new monitoring method to aid clinicians in guiding MV treatment. These are the first such maps generated and they thus show unique results in high resolution. The model is limited to a constant respiratory resistance throughout inspiration which may not be valid in some cases. However, trends match clinical expectation and the results highlight both the subject-specificity of the model, as well as significant inter-subject variability.

Keywords:
Mechanical ventilation; PEEP; Time-varying elastance; Model-based methods; ARDS; Monitoring