Abstract
Mechanical ventilation (MV) is used in the intensive care unit (ICU) to treat patients with respiratory failure. However, MV settings are not standardized due to significant inter- and intra- patient variability in response to care, leading to variability in care, outcome, and cost. There is thus a need to personalize MV. This research extends a single compartment lung mechanics model with physiologically relevant basis functions, to identify patient-specific lung mechanics and predict response to changes in MV care. The nonlinear evolution of pulmonary elastance as positive-end-expiratory pressure (PEEP) changes is captured by a physiologically relevant, simplified compensatory equation as a function of PEEP and pressure identification error at the baseline PEEP level. It allows both patient-specific and general prediction of lung elastance of higher PEEP. The prediction outcome is validated with data from two volume-controlled ventilation (VCV) trials and one pressure-controlled ventilation (PCV) trial, where the biggest PEEP prediction interval is a clinically unrealistic 20cmH(2)O, comprising 210 prediction cases over 36 patients (22 VCV; 14 PCV). Predicted absolute peak inspiratory pressure (PIP) errors are within 1.0cmH(2)O and 3.3cmH(2)O for 90% cases in the two VCV trials, while predicted peak inspiratory tidal volume (PIV) errors are within 0.073L for 85% cases in studied PCV trial. The model presented provides a highly accurate, predictive virtual patient model across multiple MV modes and delivery methods, and over clinically unrealistically large changes. Low computational cost, and fast, easy parameterization enable model-based, predictive decision support in real-time to safely personalize and optimize MV care. Copyright (C) 2021 The Authors.
Original language | English |
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Title of host publication | IFAC PAPERSONLINE |
Publisher | Elsevier |
Pages | 127-132 |
Number of pages | 6 |
Volume | 54 |
Edition | 15 |
DOIs | |
Publication status | Published - 2021 |
Event | 11th IFAC Symposium on Biological and Medical Systems - Ghent, Belgium Duration: 19 Sept 2021 → 22 Sept 2021 Conference number: 11 https://bms2021.ugent.be/ |
Symposium
Symposium | 11th IFAC Symposium on Biological and Medical Systems |
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Country/Territory | Belgium |
City | Ghent |
Period | 19/09/21 → 22/09/21 |
Internet address |
Keywords
- Mechanical ventilation
- PEEP
- Respiratory mechanics
- Elastance
- Prediction
- VILI
- Basis function
- System identification
- Virtual patient
- PRESSURE
- MODEL