Frontiers in Medicine (Oct 2024)

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

  • Brijesh V. Patel,
  • Brijesh V. Patel,
  • Sharon Mumby,
  • Nicholas Johnson,
  • Rhodri Handslip,
  • Sunil Patel,
  • Teresa Lee,
  • Martin S. Andersen,
  • Emanuela Falaschetti,
  • Ian M. Adcock,
  • Danny F. McAuley,
  • Masao Takata,
  • Thomas Staudinger,
  • Dan S. Karbing,
  • Matthieu Jabaudon,
  • Peter Schellongowski,
  • Stephen E. Rees,
  • On behalf of the DeVENT Study Group

DOI
https://doi.org/10.3389/fmed.2024.1473629
Journal volume & issue
Vol. 11

Abstract

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BackgroundAcute 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.MethodsThis 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.ResultsA 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.ConclusionThe 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 registrationclinicaltrials.gov, NCT04115709.

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