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Estimation of Inspiratory Respiratory Elastance Using Expiratory Data
Howe, S. L.; Chase, J. G.; Redmond, D. P. et al.
2018In IFAC-PapersOnLine, 51 (27), p. 204-208
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Keywords :
Lungs; Mathematical models; Mechanical ventilation; Parameter identification; Respiratory elastance; Biological organs; Estimation; Identification (control systems); Respiratory mechanics; Ventilation; Conventional methods; Elastance; Linear relationships; Models of Respiratory Mechanics; Muscle activities; Spontaneous breathing; Patient treatment
Abstract :
[en] Models of respiratory mechanics can be used to titrate patient-specific mechanical ventilation (MV) settings in critical care, but often perform poorly in the presence of patient breathing effort. Respiratory mechanics are conventionally calculated using only inspiratory data. Muscle activity is normally assumed relatively minimal or absent during passive expiration regardless of the presence of inspiratory spontaneous breathing (SB) efforts. Hence, this study assesses whether expiratory lung elastance can be used to estimate inspiratory lung elastance for spontaneously breathing, reverse triggered patients. Clinical data from recruitment manoeuvres in fully sedated patients were used to determine a relationship between inspiratory and expiratory modeled lung elastance. The validity of this relationship was assessed using data recorded pre- and post- sedation from different patients. A strong, linear relationship was found between inspiratory and expiratory elastance in fully sedated patients, with gradient 1.04 [95% CI: 1.03-1.07] and intercept 1.66 [1.06-2.08] with R2 = 0.94. After adjustment according to the linear relationship, expiratory elastance produced stable estimations post sedation, with similar median and variance as inspiratory elastance. However, variation in estimates pre-sedation, although significantly improved, may be larger than clinically acceptable in some cases. The results of this study show that the typically ignored expiratory data may be able to provide insight into patient condition when conventional methods fail. Clinically, these methods could have an impact in guiding MV therapy by providing clinicians with information about lung mechanics under the effect of patient SB effort. © 2018
Disciplines :
Anesthesia & intensive care
Author, co-author :
Howe, S. L.;  Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
Chase, J. G.;  Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
Redmond, D. P.;  Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
Morton, S. E.;  Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
Kim, K. T.;  Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
Pretty, C.;  Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
Shaw, G. M.;  Department of Intensive Care, Christchurch Hospital, Christchurch, New Zealand
Tawhai, M. H.;  Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
Desaive, Thomas  ;  Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles
Language :
English
Title :
Estimation of Inspiratory Respiratory Elastance Using Expiratory Data
Publication date :
2018
Event name :
BMS 2018
Event date :
3-5 septembre 2018
Audience :
International
Journal title :
IFAC-PapersOnLine
ISSN :
2405-8971
eISSN :
2405-8963
Publisher :
Elsevier B.V.
Volume :
51
Issue :
27
Pages :
204-208
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 08 June 2020

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