Evidence map›Paper›PMID 39540041›Full record

ArticleFrontiers in medicine2024

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, Sharon Mumby, Nicholas Johnson, Rhodri Handslip, Sunil Patel, Teresa Lee, Martin S Andersen, Emanuela Falaschetti, Ian M Adcock, Danny F McAuley and 7 more

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04115709 (Decision Support System to Evaluate VENTilation in ARDS), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04115709 nacompletednot on this map

Decision Support System to Evaluate VENTilation in ARDS (DeVENT)

TypeinterventionalSponsorImperial College LondonRan2020 to 2021Enrolled95ConditionsAcute Respiratory Distress SyndromeArmsBeacon Caresystem device with advice, Beacon Caresystem device without advice activated
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Observational
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Brijesh V PatelDivision of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.
Sharon MumbyAirway Disease, National, Heart and Lung Institute, Imperial College, London, United Kingdom.
Nicholas JohnsonImperial Clinical Trials Unit, Stadium House, London, United Kingdom.
Rhodri HandslipDivision of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.
Sunil PatelDivision of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.
Teresa LeeDivision of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.
Martin S AndersenDepartment of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark.
Emanuela FalaschettiImperial Clinical Trials Unit, Stadium House, London, United Kingdom.
Ian M AdcockAirway Disease, National, Heart and Lung Institute, Imperial College, London, United Kingdom.
Danny F McAuleyWellcome-Wolfson Institute for Experimental Medicine, Queen's University, Belfast, United Kingdom.
Masao TakataDivision of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.
Thomas StaudingerDepartment of Medicine I, ICU 13.i2, Medical University of Vienna, Vienna, Austria.
Dan S KarbingDepartment of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark.
Matthieu JabaudonDepartment of Perioperative Medicine, University Hospital of Clermont-Ferrand, GReD, Université Clermont Auvergne, CNRS, INSERM, Clermont-Ferrand, France.
Peter SchellongowskiDepartment of Medicine I, ICU 13.i2, Medical University of Vienna, Vienna, Austria.
Stephen E ReesDepartment of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark.
DeVENT Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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; 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.

Indexed as

ARDSclinical decision supportdriving pressuremechanical ventilationrespiratory mechanics

Identifiers

PMID39540041
PMCPMC11559429

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.