Anand, D Vijay;
Teixeira Cabeleira, Manuel;
Black, Claire;
Diaz-Zuccarini, Vanessa;
Ovenden, Nicholas C;
(2025)
A feedback-driven ventilation model for assessing airway secretions in mechanically ventilated patients.
Frontiers in Physiology
, 16
, Article 1612501. 10.3389/fphys.2025.1612501.
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Abstract
Introduction: A mechanistic compartmental model with a feedback-driven simulation framework was developed to investigate the impact of airway secretion accumulation and its removal on the respiratory dynamics of mechanically ventilated patients. Understanding these dynamics is essential for secretion management and improving respiratory care in the intensive care unit (ICU). // Methods: The model simulates pressure support ventilation by incorporating airway resistances, lung and chest wall compliances, and patient effort via a dynamic respiratory muscle pressure term, enabling realistic modelling of patient-ventilator interaction. To validate the model, simulated waveforms were compared against clinical waveform recordings. Waveform features sensitive to secretion-related changes, as indicated by the model, were then extracted from the patient waveform recordings. The Wasserstein distance metric was used to quantify shifts in pre- and post-suction feature distributions, and unsupervised clustering was applied to identify distinct patient groups corresponding to low, medium, and high secretion levels. // Results: The simulations revealed characteristic changes in ventilator waveforms associated with secretion accumulation, including reduced inspiratory flow and prolonged expiration. Analysis of patient data using clustering methods identified distinct groups corresponding to low, medium, and high levels of secretion. Further, we introduce a model-informed secretion index derived from the simulations and patient data, enabling non-invasive and continuous monitoring of secretion accumulation at the bedside. // Conclusions: This study demonstrates the potential of physiology-informed, model-based approaches for real-time assessment of secretion accumulation in mechanically ventilated patients. The proposed framework supports personalized respiratory care by providing clinicians with data-driven insights into secretion accumulation, paving the way for more precise secretion management strategies in the ICU.
| Type: | Article |
|---|---|
| Title: | A feedback-driven ventilation model for assessing airway secretions in mechanically ventilated patients |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fphys.2025.1612501 |
| Publisher version: | https://doi.org/10.3389/fphys.2025.1612501 |
| Language: | English |
| Additional information: | Copyright © 2025 Anand, Teixeira Cabeleira, Black, Diaz-Zuccarini and Ovenden. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | Mechanical ventilation, airway clearance, secretion management, compartmental model, ventilator waveforms |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10211539 |
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