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Modeling mechanical ventilation in silico—potential and pitfalls
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Hannon, David M., Mistry, Sonal, Das, Anup, Saffaran, Sina, Laffey, John G., Brook, Bindi S., Hardman, Jonathan G. and Bates, Declan G. (2022) Modeling mechanical ventilation in silico—potential and pitfalls. Seminars in Respiratory and Critical Care Medicine, 43 (3). pp. 335-345. doi:10.1055/s-0042-1744446 ISSN 1098-9048.
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Official URL: https://doi.org/10.1055/s-0042-1744446
Abstract
Computer simulation offers a fresh approach to traditional medical research that is particularly well suited to investigating issues related to mechanical ventilation. Patients receiving mechanical ventilation are routinely monitored in great detail, providing extensive high-quality data-streams for model design and configuration. Models based on such data can incorporate very complex system dynamics that can be validated against patient responses for use as investigational surrogates. Crucially, simulation offers the potential to “look inside” the patient, allowing unimpeded access to all variables of interest. In contrast to trials on both animal models and human patients, in silico models are completely configurable and reproducible; for example, different ventilator settings can be applied to an identical virtual patient, or the same settings applied to different patients, to understand their mode of action and quantitatively compare their effectiveness. Here, we review progress on the mathematical modeling and computer simulation of human anatomy, physiology, and pathophysiology in the context of mechanical ventilation, with an emphasis on the clinical applications of this approach in various disease states. We present new results highlighting the link between model complexity and predictive capability, using data on the responses of individual patients with acute respiratory distress syndrome to changes in multiple ventilator settings. The current limitations and potential of in silico modeling are discussed from a clinical perspective, and future challenges and research directions highlighted.
Item Type: | Journal Article | ||||||||||||
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Subjects: | R Medicine > RC Internal medicine | ||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||||
SWORD Depositor: | Library Publications Router | ||||||||||||
Library of Congress Subject Headings (LCSH): | Artificial respiration -- Mathematical models, Artificial respiration -- Computer simulation | ||||||||||||
Journal or Publication Title: | Seminars in Respiratory and Critical Care Medicine | ||||||||||||
Publisher: | Georg Thieme | ||||||||||||
ISSN: | 1098-9048 | ||||||||||||
Official Date: | 21 April 2022 | ||||||||||||
Dates: |
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Volume: | 43 | ||||||||||||
Number: | 3 | ||||||||||||
Page Range: | pp. 335-345 | ||||||||||||
DOI: | 10.1055/s-0042-1744446 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 24 May 2022 | ||||||||||||
Date of first compliant Open Access: | 21 April 2023 | ||||||||||||
RIOXX Funder/Project Grant: |
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