[en] BACKGROUND: Respiratory system modelling can aid clinical decision making during mechanical ventilation (MV) in intensive care. However, spontaneous breathing (SB) efforts can produce entrained "M-wave" airway pressure waveforms that inhibit identification of accurate values for respiratory system elastance and airway resistance. A pressure wave reconstruction method is proposed to accurately identify respiratory mechanics, assess the level of SB effort, and quantify the incidence of SB effort without uncommon measuring devices or interruption to care. METHODS: Data from 275 breaths aggregated from all mechanically ventilated patients at Christchurch Hospital were used in this study. The breath specific respiratory elastance is calculated using a time-varying elastance model. A pressure reconstruction method is proposed to reconstruct pressure waves identified as being affected by SB effort. The area under the curve of the time-varying respiratory elastance (AUC Edrs) are calculated and compared, where unreconstructed waves yield lower AUC Edrs. The difference between the reconstructed and unreconstructed pressure is denoted as a surrogate measure of SB effort. RESULTS: The pressure reconstruction method yielded a median AUC Edrs of 19.21 [IQR: 16.30-22.47]cmH2Os/l. In contrast, the median AUC Edrs for unreconstructed M-wave data was 20.41 [IQR: 16.68-22.81]cmH2Os/l. The pressure reconstruction method had the least variability in AUC Edrs assessed by the robust coefficient of variation (RCV)=0.04 versus 0.05 for unreconstructed data. Each patient exhibited different levels of SB effort, independent from MV setting, indicating the need for non-invasive, real time assessment of SB effort. CONCLUSION: A simple reconstruction method enables more consistent real-time estimation of the true, underlying respiratory system mechanics of a SB patient and provides the surrogate of SB effort, which may be clinically useful for clinicians in determining optimal ventilator settings to improve patient care.
Disciplines :
Anesthesia & intensive care
Author, co-author :
Damanhuri, Nor Salwa
Chiew, Yeong Shiong
Othman, Nor Azlan
Docherty, Paul D.
Pretty, Christopher G.
Shaw, Geoffrey M.
Desaive, Thomas ; Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles
Chase, J. Geoffrey
Language :
English
Title :
Assessing respiratory mechanics using pressure reconstruction method in mechanically ventilated spontaneous breathing patient.
Publication date :
2016
Journal title :
Computer Methods and Programs in Biomedicine
ISSN :
0169-2607
eISSN :
1872-7565
Publisher :
Elsevier, Limerick, Ireland
Volume :
130
Pages :
175-85
Peer reviewed :
Peer Reviewed verified by ORBi
Commentary :
Copyright (c) 2016 Elsevier Ireland Ltd. All rights reserved.
t Sundaresan A., Chase J.G. Positive end expiratory pressure in patients with acute respiratory distress syndrome - the past, present and future. Biomed. Signal Process. Control 2012, 7:93-103.
Lauzon A., Bates J. Estimation of time-varying respiratory mechanical parameters by recursive least squares. J. Appl. Physiol. 1991, 71:1159-1165.
Sundaresan A., Yuta T., Hann C.E., Geoffrey Chase J., Shaw G.M. A minimal model of lung mechanics and model-based markers for optimizing ventilator treatment in ARDS patients. Comput. Methods Progr. Biomed. 2009, 95:166-180.
Keith G., Hickling The pressure-volume curve is greatly modified by recruitment. a mathematical model of ARDS lungs. Am. J. Respir. Crit. Care Med. 1998, 158:194-202.
Bates J.H.T. Lung Mechanics: An Inverse Modeling Approach 2009, Cambridge University Press.
Brochard L., Martin G.S., Blanch L., Pelosi P., Belda F.J., Jubran A., Gattinoni L., Mancebo J., Ranieri V.M., Richard J. Clinical review: respiratory monitoring in the ICU-a consensus of 16. Crit. Care 2012, 16:219.
Donovan G.M. Multiscale mathematical models of airway constriction and disease. Pulm. Pharmacol. Ther. 2011, 24:533-539.
Tawhai M.H., Hunter P., Tschirren J., Reinhardt J., McLennan G., Hoffman E.A. CT-based geometry analysis and finite element models of the human and ovine bronchial tree. J. Appl. Physiol. 2004, 97:2310-2321.
Kitaoka H., Nieman G.F., Fujino Y., Carney D., DiRocco J., Kawase I. A 4-dimensional model of the alveolar structure. J. Physiol. Sci. 2007, 57:175-185.
Grinnan D.C., Truwit J.D. Clinical review: respiratory mechanics in spontaneous and assisted ventilation. Crit. Care 2005, 9:472.
Chiew Y.S., Pretty C., Docherty P.D., Lambermont B., Shaw G.M., Desaive T., Chase J.G. Time-varying respiratory system elastance: a physiological model for patients who are spontaneously breathing. PLOS ONE 2015, 10.
Akoumianaki E., Lyazidi A., Rey N., Matamis D., Perez-Martinez N., Giraud R., Mancebo J., Brochard L., Richard J.-C.M. Mechanical ventilation-induced reverse-triggered breaths reverse triggering a frequently unrecognized form of neuromechanical coupling. Chest J. 2013, 143:927-938.
Damanhuri N., Chiew Y., Othman N., Docherty P., Shaw G., Chase J. Pressure reconstruction method for spontaneous breathing effort monitoring. Crit. Care 2015, 19:P259.
Schranz C., Docherty P.D., Chiew Y.S., Moller K., Chase J.G. Iterative integral parameter identification of a respiratory mechanics model. Biomed. Eng. Online 2012, 11:38.
Benditt J.O. Esophageal and gastric pressure measurements. Respir. Care 2005, 50:68-77.
Talmor D., Sarge T., O'Donnell C.R., Ritz R., Malhotra A., Lisbon A., Loring S.H. Esophageal and transpulmonary pressures in acute respiratory failure. Crit. Care Med. 2006, 34:1389.
Khirani S., Polese G., Aliverti A., Appendini L., Nucci G., Pedotti A., Colledan M., Lucianetti A., Baconnier P., Rossi A. On-line monitoring of lung mechanics during spontaneous breathing: a physiological study. Respir. Med. 2010, 104:463-471.
Piquilloud L., Vignaux L., Bialais E., Roeseler J., Sottiaux T., Laterre P.-F., Jolliet P., Tassaux D. Neurally adjusted ventilatory assist improves patient-ventilator interaction. Intensive Care Med. 2011, 37:263-271.
van Drunen E.J., Chiew Y.S., Pretty C., Shaw G.M., Lambermont B., Janssen N., Chase J.G., Desaive T. Visualisation of time-varying respiratory system elastance in experimental ARDS animal models. BMC Pulm. Med. 2014, 14:33.
Lucangelo U., Bernabe F., Blanch L. Lung mechanics at the bedside: make it simple. Curr. Opin. Crit. Care 2007, 13:64-72.
Szlavecz A., Chiew Y.S., Redmond D., Beatson A., Glassenbury D., Corbett S., Major V., Pretty C., Shaw G.M., Benyo B. The Clinical Utilisation of Respiratory Elastance Software (CURE Soft): a bedside software for real-time respiratory mechanics monitoring and mechanical ventilation management. Biomed. Eng. Online 2014, 13:140.
Davidson S.M., Redmond D.P., Laing H., White R., Radzi F., Chiew Y.S., Poole S.F., Damanhuri N.S., Desaive T., Shaw G.M. Clinical utilisation of respiratory elastance (CURE): pilot trials for the optimisation of mechanical ventilation settings for the critically Ill. World Congress 2014, 8403-8408.
Force A.D.T. Acute respiratory distress syndrome. J. Am. Med. Assoc. 2012, 307:2526-2533.
Hann C.E., Chase J.G., Lin J., Lotz T., Doran C.V., Shaw G.M. Integral-based parameter identification for long-term dynamic verification of a glucose-insulin system model. Comput. Methods Progr. Biomed. 2005, 77:259-270.
Docherty P.D., Chase J.G., David T. Characterisation of the iterative integral parameter identification method. Med. Biol. Eng. Comput. 2012, 50:127-134.
Chiew Y.S., Chase J.G., Shaw G., Sundaresan A., Desaive T. Model-based PEEP optimisation in mechanical ventilation. Biomed. Eng. Online 2011, 10:111.
Kress J.P., Pohlman A.S., O'Connor M.F., Hall J.B. Daily interruption of sedative infusions in critically ill patients undergoing mechanical ventilation. N. Engl. J. Med. 2000, 342:1471-1477.
Ostermann M.E., Keenan S.P., Seiferling R.A., Sibbald W.J. Sedation in the intensive care unit: a systematic review. J. Am. Med. Assoc. 2000, 283:1451-1459.
Boles J.-M., Bion J., Connors A., Herridge M., Marsh B., Melot C., Pearl R., Silverman H., Stanchina M., Vieillard-Baron A. Weaning from mechanical ventilation. Eur. Respir. J. 2007, 29:1033-1056.
Esteban A., Alia I., Ibanez J., Benito S., Tobin M.J. Modes of mechanical ventilation and weaning. A national survey of Spanish hospitals. Chest J. 1994, 106:1188-1193.
Randolph A.G., Clemmer T.P., East T.D., Kinder A.T., Orme J.F., Wallace C.J., Morris A.H. Evaluation of compliance with a computerized protocol: weaning from mechanical ventilator support using pressure support. Comput. Methods Progr. Biomed. 1998, 57:201-215.
Marini J.J. Spontaneously regulated vs. controlled ventilation of acute lung injury/acute respiratory distress syndrome. Curr. Opin. Crit. Care 2011, 17:24-29.
Kogler V.M. Advantage of spontaneous breathing in patients with respiratory failure. Signa Vitae 2009, 4.
Putensen C., Norbert J., Mutz G., Putensen-Himmer J., Zinserling Spontaneous breathing during ventilatory support improves ventilation-perfusion distributions in patients with acute respiratory distress syndrome. Am. J. Respir. Crit. Care Med. 1999, 159:1241-1248.