Title |
Can computer simulators accurately represent the pathophysiology of individual COPD patients?
|
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Published in |
Intensive Care Medicine Experimental, September 2014
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DOI | 10.1186/s40635-014-0023-0 |
Pubmed ID | |
Authors |
Wenfei Wang, Anup Das, Tayyba Ali, Oanna Cole, Marc Chikhani, Mainul Haque, Jonathan G Hardman, Declan G Bates |
Abstract |
Computer simulation models could play a key role in developing novel therapeutic strategies for patients with chronic obstructive pulmonary disease (COPD) if they can be shown to accurately represent the pathophysiological characteristics of individual patients. We evaluated the capability of a computational simulator to reproduce the heterogeneous effects of COPD on alveolar mechanics as captured in a number of different patient datasets. Our results show that accurately representing the pathophysiology of individual COPD patients necessitates the use of simulation models with large numbers (up to 200) of compartments for gas exchange. The tuning of such complex simulation models 'by hand' to match patient data is not feasible, and thus we present an automated approach based on the use of global optimization algorithms and high-performance computing. Using this approach, we are able to achieve extremely close matches between the simulator and a range of patient data including PaO2, PaCO2, pulmonary deadspace fraction, pulmonary shunt fraction, and ventilation/perfusion (<Vdot>/Q) curves. Using the simulator, we computed combinations of ventilator settings that optimally manage the trade-off between ensuring adequate gas exchange and minimizing the risk of ventilator-associated lung injury for an individual COPD patient. Our results significantly strengthen the credibility of computer simulation models as research tools for the development of novel management protocols in COPD and other pulmonary disease states. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 5% |
Unknown | 19 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 25% |
Student > Master | 3 | 15% |
Lecturer | 1 | 5% |
Student > Doctoral Student | 1 | 5% |
Student > Bachelor | 1 | 5% |
Other | 5 | 25% |
Unknown | 4 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 7 | 35% |
Medicine and Dentistry | 3 | 15% |
Nursing and Health Professions | 2 | 10% |
Unspecified | 1 | 5% |
Mathematics | 1 | 5% |
Other | 1 | 5% |
Unknown | 5 | 25% |