An analysis of the impact of the inclusion of expiration data on the fitting of a predictive pulmonary elastance model

Simple item page
dc.contributor.authorMorton, Sophie Elizabeth
dc.contributor.authorDocherty PD
dc.contributor.authorDickson JL
dc.contributor.authorChase, Geoff
dc.date.accessioned2019-11-12T22:33:29Z
dc.date.available2019-11-12T22:33:29Z
dc.date.issued2018en
dc.date.updated2019-03-13T15:16:59Z
dc.description.abstractMechanical ventilation is a primary therapy for patients with respiratory failure. However, incorrect ventilator settings can cause lung damage. Optimising ventilation while minimising risk is complex in practice. A common lung protective strategy is to titrate positive end-expiratory pressure (PEEP) to the point of minimum elastance. This process can result in additional available lung volume due to alveolar recruitment but comes with the risk of subjecting the lungs to excessive pressure and lung damage. Predictive elastance models can mitigate this risk by estimating airway pressure at a higher PEEP level. Due to the increased risk of barotrauma during inspiration, many models exclude expiration data. However, this section of the breath can include useful information about lung mechanics. This research investigates the impact that including expiration data into the fitting of a validated predictive elastance model will have on its ability to predict peak inspiratory pressure. Results showed that expiration data did not improve the efficacy of the model in this case with an increase in error (median (%)) of predicting peak inspiratory pressure through an increase in PEEP of 8 cmH2O from 6% to 16%.en
dc.identifier.citationMorton SE, Docherty PD, Dickson JL, Chase G (2018). An analysis of the impact of the inclusion of expiration data on the fitting of a predictive pulmonary elastance model. Aachen, Germany: 52nd Annual Conference of the German Society for Biomedical Engineering (BMT 2018). 26/09/2018-28/09/2018. Current Directions in Biomedical Engineering. 4. 1. 255-258.en
dc.identifier.doihttps://doi.org/10.1515/cdbme-2018-0062
dc.identifier.urihttp://hdl.handle.net/10092/17614
dc.language.isoen
dc.rightsOpen Access. © 2018 Sophie Morton et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.en
dc.subjectPulmonary elastanceen
dc.subjectMechanical ventilationen
dc.subjectsystem identificationen
dc.subjectpredictionen
dc.subject.anzsrcFields of Research::40 - Engineering::4003 - Biomedical engineering::400303 - Biomechanical engineeringen
dc.subject.anzsrcFields of Research::32 - Biomedical and clinical sciences::3202 - Clinical sciences::320212 - Intensive careen
dc.titleAn analysis of the impact of the inclusion of expiration data on the fitting of a predictive pulmonary elastance modelen
dc.typeConference Contributions - Publisheden
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
[Current Directions in Biomedical Engineering] An analysis of the impact of the inclusion of expiration data on the fitting of a predictive pulmonary elastance model.pdf
Size:
500.77 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Engineering: Conference Contributions