Estimating the true respiratory mechanics during asynchronous pressure controlled ventilation

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dc.contributor.authorKannangara, D.O.
dc.contributor.authorNewberry, F.
dc.contributor.authorHowe, S.
dc.contributor.authorMajor, V.
dc.contributor.authorRedmond, D.
dc.contributor.authorSzlavecs, A.
dc.contributor.authorChiew, Y.S.
dc.contributor.authorPretty, C.
dc.contributor.authorBenyo, B.
dc.contributor.authorShaw, Geoff
dc.contributor.authorChase, Geoff
dc.date.accessioned2019-09-23T20:07:05Z
dc.date.available2019-09-23T20:07:05Z
dc.date.issued2016en
dc.description.abstractMechanical ventilation (MV) therapy partially or fully replaces the work of breathing in patients with respiratory failure. Respiratory mechanics during pressure controlled (PC) or pressure support (PS) are often not estimated due to variability induced by patient’s spontaneous breathing effort (SB) or asynchronous events (AEs). Thus for non-invasive model based MV with PC/PS, there is a need for improved estimation of respiratory mechanics. An algorithm is proposed that allows for the improvement of respiratory system mechanics estimation during pressure controlled ventilation, while providing a means of quantifying AE magnitude as one indicator of patient-ventilator interaction, which may be valuable to clinicians to monitor patient response to care. For testing, 10 retrospective airway pressure and flow data samples were obtained from 6 MV patients, with each data sample containing 450 500 breaths. All data samples with AE present experienced a decrease in 5th to 95th range (Range90) and mean absolute deviation (MAD) for the estimated respiratory system elastance after reconstruction. These results suggested improved in respiratory mechanics estimation during pressure controlled ventilation. The median [maximum (max), minimum (min)] decrease in MAD was 29.4% (51%, 18.6%), and the median (max, min) decrease in Range90 divided by median respiratory system elastance was 30.7% (48.8%, 6.4%). The algorithm is robust to many different spontaneous breathing efforts, asynchrony shapes and types. The proposed algorithm demonstrates the potential to effectively improve respiratory mechanics and quantify the magnitude of AEs.en
dc.identifier.citationKannangara, D.O., Newberry, F., Howe, S., Major, V., Redmond, D., Szlavecs, A., Chiew, Y.S., Pretty, C., Benyo, B., Shaw, G.M., Chase, J.G. (2016) Estimating the true respiratory mechanics during asynchronous pressure controlled ventilation. Biomedical Signal Processing and Control, 30, pp. 70-78.en
dc.identifier.doihttps://doi.org/10.1016/j.bspc.2016.06.014
dc.identifier.issn1746-8094
dc.identifier.urihttp://hdl.handle.net/10092/17256
dc.language.isoen
dc.publisherUniversity of Canterbury. Mathematics and Statisticsen
dc.publisherUniversity of Canterbury. Mechanical Engineeringen
dc.rightsCreative Commons Attribution Non-Commercial No Derivatives Licenseen
dc.rights.urihttps://hdl.handle.net/10092/17651
dc.subject.anzsrcFields of Research::40 - Engineering::4003 - Biomedical engineering::400303 - Biomechanical engineeringen
dc.titleEstimating the true respiratory mechanics during asynchronous pressure controlled ventilationen
dc.typeJournal Articleen
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