Decision support system to evaluate ventilation in the acute respiratory distress syndrome (DeVENT study)-trial protocol

Brijesh Patel, Sharon Mumby, Nicholas Johnson, Emanuela Falaschetti, Jorgen Hansen, Ian Adcock, Danny McAuley, Masao Takata, Dan S Karbing, Matthieu Jabaudon, Peter Schellengowski, Stephen E Rees, DeVENT study group, Brijesh Patel, Sharon Mumby, Nicholas Johnson, Emanuela Falaschetti, Jorgen Hansen, Ian Adcock, Danny McAuley, Masao Takata, Dan S Karbing, Matthieu Jabaudon, Peter Schellengowski, Stephen E Rees, DeVENT study group

Abstract

Background: The acute respiratory distress syndrome (ARDS) occurs in response to a variety of insults, and mechanical ventilation is life-saving in this setting, but ventilator-induced lung injury can also contribute to the morbidity and mortality in the condition. The Beacon Caresystem is a model-based bedside decision support system using mathematical models tuned to the individual patient's physiology to advise on appropriate ventilator settings. Personalised approaches using individual patient description may be particularly advantageous in complex patients, including those who are difficult to mechanically ventilate and wean, in particular ARDS.

Methods: We will conduct a multi-centre international randomised, controlled, allocation concealed, open, pragmatic clinical trial to compare mechanical ventilation in ARDS patients following application of the Beacon Caresystem to that of standard routine care to investigate whether use of the system results in a reduction in driving pressure across all severities and phases of ARDS.

Discussion: Despite 20 years of clinical trial data showing significant improvements in ARDS mortality through mitigation of ventilator-induced lung injury, there remains a gap in its personalised application at the bedside. Importantly, the protective effects of higher positive end-expiratory pressure (PEEP) were noted only when there were associated decreases in driving pressure. Hence, the pressures set on the ventilator should be determined by the diseased lungs' pressure-volume relationship which is often unknown or difficult to determine. Knowledge of extent of recruitable lung could improve the ventilator driving pressure. Hence, personalised management demands the application of mechanical ventilation according to the physiological state of the diseased lung at that time. Hence, there is significant rationale for the development of point-of-care clinical decision support systems which help personalise ventilatory strategy according to the current physiology. Furthermore, the potential for the application of the Beacon Caresystem to facilitate local and remote management of large numbers of ventilated patients (as seen during this COVID-19 pandemic) could change the outcome of mechanically ventilated patients during the course of this and future pandemics.

Trial registration: ClinicalTrials.gov identifier NCT04115709. Registered on 4 October 2019, version 4.0.

Keywords: COVID-19; Critical care; Decision support; Mechanical ventilation; Acute respiratory distress syndrome; Pandemic.

Conflict of interest statement

JH is chief executive officer for Mermaid Care A/S who manufacture the Beacon Caresystem.

SR and DK are minor shareholders and SR is a board member of Mermaid Care A/S who manufacture the Beacon Caresystem.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Study schematic of the randomised, controlled, allocation concealed, open, pragmatic clinical study investigating the effect of the Beacon Caresystem on ventilation in ARDS
Fig. 2
Fig. 2
Prone position and recruitment manoeuvre flow, including intermittent ALPE procedures
Fig. 3
Fig. 3
Data workflow process
Fig. 4
Fig. 4
Composition of trial co-ordination

References

    1. Network ARDS. Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. The Acute Respiratory Distress Syndrome Network. N Engl J Med. 2000;342(18):1301–1308. doi: 10.1056/NEJM200005043421801.
    1. Amato MBP, Meade MO, Slutsky AS, Brochard L, Costa ELV, Schoenfeld DA, Stewart TE, Briel M, Talmor D, Mercat A, Richard JCM, Carvalho CRR, Brower RG. Driving pressure and survival in the acute respiratory distress syndrome. N Engl J Med. 2015;372(8):747–755. doi: 10.1056/NEJMsa1410639.
    1. Lung NH, Blood Institute Acute Respiratory Distress Syndrome ARDS Clinical Trials Network, Wiedemann HP, Wheeler AP, Bernard GR, Thompson BT, Hayden D, et al. Comparison of two fluid-management strategies in acute lung injury. N Engl J Med. 2006;354(24):2564–2575. doi: 10.1056/NEJMoa062200.
    1. Briel M, Meade M, Mercat A, Brower RG, Talmor D, Walter SD, Slutsky AS, Pullenayegum E, Zhou Q, Cook D, Brochard L, Richard JCM, Lamontagne F, Bhatnagar N, Stewart TE, Guyatt G. Higher vs lower positive end-expiratory pressure in patients with acute lung injury and acute respiratory distress syndrome: systematic review and meta-analysis. JAMA. 2010;303(9):865–873. doi: 10.1001/jama.2010.218.
    1. Guerin C, Reignier J, Richard J-C, Beuret P, Gacouin A, Boulain T, et al. Prone positioning in severe acute respiratory distress syndrome. N Engl J Med. 2013;368(23):2159–2168. doi: 10.1056/NEJMoa1214103.
    1. Needham DM, Colantuoni E, Mendez-Tellez PA, Dinglas VD, Sevransky JE, Dennison Himmelfarb CR, et al. Lung protective mechanical ventilation and two year survival in patients with acute lung injury: prospective cohort study. BMJ. 2012;344(apr05 2):e2124. doi: 10.1136/bmj.e2124.
    1. Cavalcanti AB, Suzumura ÉA, Laranjeira LN, Paisani D, de M, Damiani LP, et al. Effect of lung recruitment and titrated positive end-expiratory pressure (PEEP) vs low PEEP on mortality in patients with acute respiratory distress syndrome: a randomized clinical trial. JAMA. 2017;318(14):1335–1345. doi: 10.1001/jama.2017.14171.
    1. Zampieri FG, Costa EL, Iwashyna TJ, Carvalho CRR, Damiani LP, Taniguchi LU, Amato MBP, Cavalcanti AB. Heterogeneous effects of alveolar recruitment in acute respiratory distress syndrome: a machine learning reanalysis of the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial. Br J Anaesth. 2019;5(1):88–95. doi: 10.1016/j.bja.2019.02.026.
    1. Rees SE, Allerød C, Murley D, Zhao Y, Smith BW, Kjaergaard S, et al. Using physiological models and decision theory for selecting appropriate ventilator settings. J Clin Monit Comput. 2006;20(6):421–429. doi: 10.1007/s10877-006-9049-5.
    1. Rees SE, Karbing DS. Determining the appropriate model complexity for patient-specific advice on mechanical ventilation. Biomed Tech. 2017;62(2):183–198. doi: 10.1515/bmt-2016-0061.
    1. Spadaro S, Karbing DS, Mauri T, Marangoni E, Mojoli F, Valpiani G, Carrieri C, Ragazzi R, Verri M, Rees SE, Volta CA. Effect of positive end-expiratory pressure on pulmonary shunt and dynamic compliance during abdominal surgery. Br J Anaesth. 2016;116(6):855–861. doi: 10.1093/bja/aew123.
    1. Spadaro S, Grasso S, Karbing DS, Fogagnolo A, Contoli M, Bollini G, Ragazzi R, Cinnella G, Verri M, Cavallesco NG, Rees SE, Volta CA. Physiologic evaluation of ventilation perfusion mismatch and respiratory mechanics at different positive end-expiratory pressure in patients undergoing protective one-lung ventilation. Anesthesiology. 2018;128(3):531–538. doi: 10.1097/ALN.0000000000002011.
    1. Kjaergaard S, Rees SE, Nielsen JA, Freundlich M, Thorgaard P, Andreassen S. Modelling of hypoxaemia after gynaecological laparotomy. Acta Anaesthesiol Scand. 2001;45(3):349–356. doi: 10.1034/j.1399-6576.2001.045003349.x.
    1. Karbing DS, Kjaergaard S, Andreassen S, Espersen K, Rees SE. Minimal model quantification of pulmonary gas exchange in intensive care patients. Med Eng Phys. 2011;33(2):240–248. doi: 10.1016/j.medengphy.2010.10.007.
    1. Karbing DS, Kjaergaard S, Smith BW, Espersen K, Allerød C, Andreassen S, et al. Variation in the PaO2/FiO2 ratio with FiO2: mathematical and experimental description, and clinical relevance. Crit Care. 2007;11(6):R118. doi: 10.1186/cc6174.
    1. Kjaergaard S, Rees S, Malczynski J, Nielsen JA, Thorgaard P, Toft E, Andreassen S. Non-invasive estimation of shunt and ventilation-perfusion mismatch. Intensive Care Med. 2003;29(5):727–734. doi: 10.1007/s00134-003-1708-0.
    1. Rees SE, Kjaergaard S, Andreassen S, Hedenstierna G. Reproduction of inert gas and oxygenation data: a comparison of the MIGET and a simple model of pulmonary gas exchange. Intensive Care Med. 2010;36(12):2117–2124. doi: 10.1007/s00134-010-1981-7.
    1. Rees SE, Kjaergaard S, Andreassen S, Hedenstierna G. Reproduction of MIGET retention and excretion data using a simple mathematical model of gas exchange in lung damage caused by oleic acid infusion. J Appl Physiol. 2006;101(3):826–832. doi: 10.1152/japplphysiol.01481.2005.
    1. Rees SE, Andreassen S. Mathematical models of oxygen and carbon dioxide storage and transport: the acid-base chemistry of blood. Crit Rev Biomed Eng. 2005;33(3):209–264. doi: 10.1615/CritRevBiomedEng.v33.i3.10.
    1. Rees SE, Klaestrup E, Handy J, Andreassen S, Kristensen SR. Mathematical modelling of the acid-base chemistry and oxygenation of blood: a mass balance, mass action approach including plasma and red blood cells. Eur J Appl Physiol. 2010;108(3):483–494. doi: 10.1007/s00421-009-1244-x.
    1. Larraza S, Dey N, Karbing DS, Jensen JB, Nygaard M, Winding R, Rees SE. A mathematical model approach quantifying patients' response to changes in mechanical ventilation: evaluation in volume support. Med Eng Phys. 2015;37(4):341–349. doi: 10.1016/j.medengphy.2014.12.006.
    1. Karbing DS, Spadaro S, Dey N, Ragazzi R, Marangoni E, Dalla Corte F, Moro F, Lodahl D, Hansen NS, Winding R, Rees SE, Volta CA. An open-loop, physiologic model-based decision support system can provide appropriate ventilator settings. Crit Care Med. 2018;46(7):e642–e648. doi: 10.1097/CCM.0000000000003133.
    1. Spadaro S, Karbing DS, Dalla Corte F, Mauri T, Moro F, Gioia A, Volta CA, Rees SE. An open-loop, physiological model based decision support system can reduce pressure support while acting to preserve respiratory muscle function. J Crit Care. 2018;48:407–413. doi: 10.1016/j.jcrc.2018.10.003.

Source: PubMed

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