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

Abstract

BackgroundPatients 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.MethodsThe 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.ResultsSix 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.ConclusionsReal-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.

Feasibility of titrating PEEP to minimum elastance for mechanically ventilated patients

“…Thus, the E rs response observed in this study may be limited to PEEP-induced recruitment and not time-dependent recruitment (if stabilization was not achieved). This limitation is also outlined in the animal trials by van Drunen et al [47]. The 10–15 breathing cycles stabilization period allowed for this trial may not be sufficient for all patients as alveoli recruitment is both PEEP- and time-dependent.…”

Identifying pressure dependent elastance in lung mechanics with reduced influence of unmodelled effects

“…Bates et al (Bates 2009) refers to two different strategies to counter that problem, either the increase in complexity of the model or introduction of nonlinear parameters. A modification of the FOM includes a non-linear time-variant dynamic elastance E(t) term (Chiew et al 2011;Guttmann et al ;van Drunen et al 2014). E(t) was determined after linear regression identification of the constant R value over a single breath.…”

Respiratory mechanics assessment for reverse-triggered breathing cycles using pressure reconstruction

“…The pressure waveforms cease to show any SB effect, illustrated in Figure 5(b). The unaltered pressure waveform will allow a good estimation of respiratory mechanics using linear regression [2,4,9]. The patient's condition should not otherwise change during transition.…”

“…Using easily measured inspiratory airway pressure and flow data, Ers and Rrs can be estimated using linear regression [2,4,9].…”

“…Model-based methods to monitor respiratory mechanics for mechanical ventilation (MV) patients can assist clinicians to guide MV treatment [1][2][3][4]. However, true respiratory mechanics can be masked by spontaneous breathing (SB) efforts and cannot be estimated in these cases without the use of invasive measuring equipment or clinical protocols [5][6][7].…”