[en] BACKGROUND: Respiratory mechanics models can aid in optimising patient-specific mechanical ventilation (MV), but the applications are limited to fully sedated MV patients who have little or no spontaneously breathing efforts. This research presents a time-varying elastance (Edrs) model that can be used in spontaneously breathing patients to determine their respiratory mechanics. METHODS: A time-varying respiratory elastance model is developed with a negative elastic component (Edemand), to describe the driving pressure generated during a patient initiated breathing cycle. Data from 22 patients who are partially mechanically ventilated using Pressure Support (PS) and Neurally Adjusted Ventilatory Assist (NAVA) are used to investigate the physiology relevance of the time-varying elastance model and its clinical potential. Edrs of every breathing cycle for each patient at different ventilation modes are presented for comparison. RESULTS: At the start of every breathing cycle initiated by patient, Edrs is < 0. This negativity is attributed from the Edemand due to a positive lung volume intake at through negative pressure in the lung compartment. The mapping of Edrs trajectories was able to give unique information to patients' breathing variability under different ventilation modes. The area under the curve of Edrs (AUCEdrs) for most patients is > 25 cmH2Os/l and thus can be used as an acute respiratory distress syndrome (ARDS) severity indicator. CONCLUSION: The Edrs model captures unique dynamic respiratory mechanics for spontaneously breathing patients with respiratory failure. The model is fully general and is applicable to both fully controlled and partially assisted MV modes.
Disciplines :
Anesthesia & intensive care
Author, co-author :
Chiew, Yeong Shiong
Pretty, Christopher
Docherty, Paul D.
LAMBERMONT, Bernard ; Centre Hospitalier Universitaire de Liège - CHU > Frais communs médecine
Shaw, Geoffrey M.
Desaive, Thomas ; Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles
Chase, J. Geoffrey
Language :
English
Title :
Time-varying respiratory system elastance: a physiological model for patients who are spontaneously breathing.
Publication date :
2015
Journal title :
PLoS ONE
eISSN :
1932-6203
Publisher :
Public Library of Science, United States - California
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Bibliography
Lucangelo U, Bernabè F, Blanch L (2007) Lung mechanics at the bedside: make it simple. Current Opinion in Critical Care 13: 64-72. doi: 10.1097/MCC.0b013e32801162df PMID: 17198051
Brochard L, Martin G, Blanch L, Pelosi P, Belda FJ, et al. (2012) Clinical review: Respiratory monitoring in the ICU-a consensus of 16. Critical Care 16: 219. doi: 10.1186/cc11146 PMID: 22546221
Benditt JO (2005) Esophageal and Gastric Pressure Measurements. Respiratory Care 50: 68-77. PMID: 15636646
Khirani S, Polese G, Aliverti A, Appendini L, Nucci G, et al. (2010) On-line monitoring of lung mechanics during spontaneous breathing: a physiological study. Respiratory Medicine 104: 463-471. doi: 10.1016/j.rmed.2009.09.014 PMID: 20096552
Gilstrap D, MacIntyre N (2013) Patient-Ventilator Interactions. Implications for Clinical Management. American Journal of Respiratory and Critical Care Medicine 188: 1058-1068. doi: 10.1164/rccm.201212-2214CI
Akoumianaki E, Lyazidi A, Rey N, Matamis D, Perez-Martinez N, et al. (2013) Mechanical ventilationinduced reverse-triggered breaths: A frequently unrecognized form of neuromechanical coupling. CHEST 143: 927-938. doi: 10.1378/chest.12-1817 PMID: 23187649
Iotti GA, Braschi A, Brunner JX, Smits T, Olivei M, et al. (1995) Respiratory mechanics by least squares fitting in mechanically ventilated patients: Applications during paralysis and during pressure support ventilation. Intensive Care Medicine 21: 406-413. doi: 10.1007/BF01707409 PMID: 7665750
Talmor D, Sarge T, Malhotra A, O'Donnell CR, Ritz R, et al. (2008) Mechanical Ventilation Guided by Esophageal Pressure in Acute Lung Injury. New England Journal of Medicine 359: 2095-2104. doi: 10.1056/NEJMoa0708638 PMID: 19001507
Kuhlen R, Putensen C (1999) Maintaining spontaneous breathing efforts during mechanical ventilatory support. Intensive Care Medicine 25: 1203-1205. doi: 10.1007/s001340051045 PMID: 10654200
Putensen C, Zech S, Wrigge H, Zinserling J, Stuber F, et al. (2001) Long-Term Effects of Spontaneous Breathing During Ventilatory Support in Patients with Acute Lung Injury. Am J Respir Crit Care Med 164: 43-49. doi: 10.1164/ajrccm.164.1.2001078 PMID: 11435237
Burchardi H (2004) Aims of sedation/analgesia. Minerva Anestesiol 70: 137-143. PMID: 15173687
Wrigge H, Zinserling J, Neumann P, Muders T, Magnusson A, et al. (2005) Spontaneous breathing with airway pressure release ventilation favors ventilation in dependent lung regions and counters cyclic alveolar collapse in oleic-acid-induced lung injury: a randomized controlled computed tomography trial. Crit Care 9: R780-R789. doi: 10.1186/cc3908 PMID: 16356227
Slutsky AS, Brochard L, Putensen C, Hering R, Wrigge H (2005) Spontaneous Breathing During Ventilatory Support in Patients with ARDS. In: Vincent J-L, editor. Mechanical Ventilation: Springer Berlin Heidelberg. pp. 353-366.
Brander L, Slutsky A (2006) Assisted spontaneous breathing during early acute lung injury. Critical Care 10: 102. doi: 10.1186/cc3953 PMID: 16420654
Kogler VM (2009) Advantage of spontaneous breathing in patients with respiratory failure. SIGNA VITAE 4.
Bates JHT (2009) Lung Mechanics: An Inverse Modeling Approach. United States of America, New York: Cambridge University Press.
Schranz C, Docherty PD, Chiew YS, Chase JG, Moller K (2012) Structural Identifiability and Practical Applicability of an Alveolar Recruitment Model for ARDS Patients. Biomedical Engineering, IEEE Transactions on 59: 3396-3404. doi: 10.1109/TBME.2012.2216526
Steimle KL, Mogensen ML, Karbing DS, Bernardino de la Serna J, Andreassen S (2011) A model of ventilation of the healthy human lung. Computer Methods and Programs in Biomedicine 101: 144-155. doi: 10.1016/j.cmpb.2010.06.017 PMID: 20655612
Docherty PD, Schranz C, Chiew Y-S, Möller K, Chase JG (2014) Reformulation of the pressuredependent recruitment model (PRM) of respiratory mechanics. Biomedical Signal Processing and Control 12: 47-53. doi: 10.1016/j.bspc.2013.12.001
Guérin C, Richard J-C (2012) Comparison of 2 Correction Methods for Absolute Values of Esophageal Pressure in Subjects With Acute Hypoxemic Respiratory Failure, Mechanically Ventilated in the ICU. Respiratory Care 57: 2045-2051. PMID: 23233496
Chiew YS, Chase JG, Shaw G, Sundaresan A, Desaive T (2011) Model-based PEEP Optimisation in Mechanical Ventilation. BioMedical Engineering OnLine 10: 111. doi: 10.1186/1475-925X-10-111 PMID: 22196749
van Drunen E, Chiew YS, Pretty C, Shaw G, Lambermont B, et al. (2014) Visualisation of time-varying respiratory system elastance in experimental ARDS animal models. BMC Pulmonary Medicine 14: 33. doi: 10.1186/1471-2466-14-33 PMID: 24581274
Chiumello D, Carlesso E, Cadringher P, Caironi P, Valenza F, et al. (2008) Lung Stress and Strain during Mechanical Ventilation for Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med 178: 346-355. doi: 10.1164/rccm.200710-1589OC PMID: 18451319
Carvalho A, Jandre F, Pino A, Bozza F, Salluh J, et al. (2007) Positive end-expiratory pressure at minimal respiratory elastance represents the best compromise between mechanical stress and lung aeration in oleic acid induced lung injury. Critical Care 11: R86. doi: 10.1186/cc6093 PMID: 17688701
Piquilloud L, Vignaux L, Bialais E, Roeseler J, Sottiaux T, et al. (2011) Neurally adjusted ventilatory assist improves patient-ventilator interaction. Intensive Care Medicine 37: 263-271. doi: 10.1007/s00134-010-2052-9 PMID: 20871978
Moorhead K, Piquilloud L, Lambermont B, Roeseler J, Chiew YS, et al. (2012) NAVA enhances tidal volume and diaphragmatic electro-myographic activity matching: a Range90 analysis of supply and demand. Journal of Clinical Monitoring and Computing: 1-10.
Zhao Z, Guttmann J, Moller K (2012) Adaptive Slice Method: A new method to determine volume dependent dynamic respiratory system mechanics. Physiol Meas 33: 51-64. doi: 10.1088/0967-3334/33/1/51 PMID: 22155927
Muramatsu K, Yukitake K, NakamuraM, Matsumoto I, Motohiro Y (2001) Monitoring of nonlinear respiratory elastance using a multiple linear regression analysis. European Respiratory Journal 17: 1158-1166. doi: 10.1183/09031936.01.00017801 PMID: 11491159
The ARDS Definition Task Force A (2012) Acute respiratory distress syndrome: The berlin definition. JAMA: The Journal of the American Medical Association 307: 2526-2533.
Alencar AM, Arold SP, Buldyrev SV, Majumdar A, Stamenovic D, et al. (2002) Physiology: Dynamic instabilities in the inflating lung. Nature 417: 809-811. doi: 10.1038/417809b PMID: 12075340
Bauer K, Brücker C (2009) The role of ventilation frequency in airway reopening. Journal of Biomechanics 42: 1108-1113. doi: 10.1016/j.jbiomech.2009.02.018 PMID: 19345364
Lauzon AM, Bates JH (1991) Estimation of time-varying respiratory mechanical parameters by recursive least squares. Journal of Applied Physiology 71: 1159-1165. PMID: 1757313
Avanzolini G, Barbini P, Cappello A, Cevenini G, Chiari L (1997) A new approach for tracking respiratory mechanical parameters in real-time. Annals of Biomedical Engineering 25: 154-163. doi: 10.1007/BF02738546 PMID: 9124729
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