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

TITLE=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

JOURNAL=Frontiers in Medicine

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2024.1473629

DOI=10.3389/fmed.2024.1473629

ISSN=2296-858X

ABSTRACT=Background. Acute respiratory distress syndrome (ARDS) is highly heterogenous, both in clinical presentation and in the physiological response of patients 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. An international, multi-centre, randomized, open-label study enrolling patients with ARDS during the COVID-19 pandemic (registered in clinicaltrials.gov (NCT04115709)), with patients randomized to having the advice of the system active (intervention) or not (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 related and device related adverse events; and number of times the advice is followed.

Results. 95 patients were randomized to this study. The DSS showed no effect in the average driving pressure between arms.  Patients in the intervention arm had statistically improved oxygenation index when in support mode ventilation (-1.41, 95% CI: -2.76, -0.08; p=0.0370). Ventilatory ratio was also 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 resulted in a significantly increased number of ventilator changes for pressure settings and respiratory frequency. 

Conclusions. The application of a physiological model-based decision support system for 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, but that that application of about 60% of advice improved the patient’s physiological state.