A randomized control trial evaluating the advice of a physiological-model/digital twin-based decision support system on mechanical ventilation in patients with acute respiratory distress syndrome.

Autor:	Patel BV; Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.; Department of Critical Care, Royal Brompton Hospital, London, United Kingdom., Mumby S; Airway Disease, National, Heart and Lung Institute, Imperial College, London, United Kingdom., Johnson N; Imperial Clinical Trials Unit, Stadium House, London, United Kingdom., Handslip R; Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom., Patel S; Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom., Lee T; Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom., Andersen MS; Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark., Falaschetti E; Imperial Clinical Trials Unit, Stadium House, London, United Kingdom., Adcock IM; Airway Disease, National, Heart and Lung Institute, Imperial College, London, United Kingdom., McAuley DF; Wellcome-Wolfson Institute for Experimental Medicine, Queen's University, Belfast, United Kingdom., Takata M; Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom., Staudinger T; Department of Medicine I, ICU 13.i2, Medical University of Vienna, Vienna, Austria., Karbing DS; Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark., Jabaudon M; Department of Perioperative Medicine, University Hospital of Clermont-Ferrand, GReD, Université Clermont Auvergne, CNRS, INSERM, Clermont-Ferrand, France., Schellongowski P; Department of Medicine I, ICU 13.i2, Medical University of Vienna, Vienna, Austria., Rees SE; Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark.
Jazyk:	angličtina
Zdroj:	Frontiers in medicine [Front Med (Lausanne)] 2024 Oct 30; Vol. 11, pp. 1473629. Date of Electronic Publication: 2024 Oct 30 (Print Publication: 2024).
DOI:	10.3389/fmed.2024.1473629
Abstrakt:	Background: Acute respiratory distress syndrome (ARDS) is highly heterogeneous, both in its clinical presentation and in the patient's physiological responses to changes in mechanical ventilator settings, such as PEEP. This study investigates the clinical efficacy of a physiological model-based ventilatory decision support system (DSS) to personalize ventilator therapy in ARDS patients. Methods: This international, multicenter, randomized, open-label study enrolled patients with ARDS during the COVID-19 pandemic. Patients were randomized to either receive active advice from the DSS (intervention) or standard care without DSS advice (control). The primary outcome was to detect a reduction in average driving pressure between groups. Secondary outcomes included several clinically relevant measures of respiratory physiology, ventilator-free days, time from control mode to support mode, number of changes in ventilator settings per day, percentage of time in control and support mode ventilation, ventilation- and device-related adverse events, and the number of times the advice was followed. Results: A total of 95 patients were randomized in this study. The DSS showed no significant effect on average driving pressure between groups. However, patients in the intervention arm had a statistically improved oxygenation index when in support mode ventilation (-1.41, 95% CI: -2.76, -0.08; p  = 0.0370). Additionally, the ventilatory ratio significantly improved in the intervention arm for patients in control mode ventilation (-0.63, 95% CI: -1.08, -0.17, p  = 0.0068). The application of the DSS led to a significantly increased number of ventilator changes for pressure settings and respiratory frequency. Conclusion: The use of a physiological model-based decision support system for providing advice on mechanical ventilation in patients with COVID-19 and non-COVID-19 ARDS showed no significant difference in driving pressure as a primary outcome measure. However, the application of approximately 60% of the DSS advice led to improvements in the patient's physiological state. Clinical Trial Registration: clinicaltrials.gov, NCT04115709. Competing Interests: SR and DK have previously been, but are no longer, shareholders of Mermaid Care A/S, who manufactured the decision support system presented here. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Patel, Mumby, Johnson, Handslip, Patel, Lee, Andersen, Falaschetti, Adcock, McAuley, Takata, Staudinger, Karbing, Jabaudon, Schellongowski and Rees.)
Databáze:	MEDLINE
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