Evidence map›Paper›PMID 25578295›Full record

ArticleCritical care (London, England)2015

Evaluation of lung recruitment maneuvers in acute respiratory distress syndrome using computer simulation.

Anup Das, Oana Cole, Marc Chikhani, Wenfei Wang, Tayyba Ali, Mainul Haque, Declan G Bates, Jonathan G Hardman

2 registry-linked trialsOpen access · goldAbstract readComparative Study
In one paragraph

Article in Critical care (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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.

NCT04297397 completednot on this mapstarted 2020, after this paper: background citation

Personalised Simulation Technologies for Optimising Treatment in the Intensive Care Unit

TypeobservationalSponsorGuy's and St Thomas' NHS Foundation TrustRan2020 to 2022Enrolled25ConditionsRespiratory Distress Syndrome, Adult, Respiratory Insufficiency
NCT05702411 naunknown statusnot on this mapstarted 2021, after this paper: background citation

Air Stacking Technique For Pulmonary Reexpansion In The Ventilator After Expiratory Pause During Aspiration In Closed System

TypeinterventionalSponsorHospital Nossa Senhora da ConceicaoRan2021 to 2023Enrolled39ConditionsCritical CareArmsAir Stacking Technique, No Air Stacking Technique
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Digital twins for chronic lung diseases.European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Article
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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

8 authors at 2 institutions in 1 country.

Anup DasSchool of Engineering, University of Warwick, Library Road, Coventry, CV4 7AL, UK. Anup.Das@warwick.ac.uk.
Oana ColeAnaesthesia & Critical Care Research Group, University of Nottingham, Derby Road, Nottingham, NG7 2UH, UK. minnnie_2000@yahoo.fr.
Marc ChikhaniAnaesthesia & Critical Care Research Group, University of Nottingham, Derby Road, Nottingham, NG7 2UH, UK. Marc.Chikhani@nottingham.ac.uk.
Wenfei WangSchool of Engineering, University of Warwick, Library Road, Coventry, CV4 7AL, UK. Wenfei.Wang@warwick.ac.uk.
Tayyba AliAnaesthesia & Critical Care Research Group, University of Nottingham, Derby Road, Nottingham, NG7 2UH, UK. Tayyba.Ali@nottingham.ac.uk.
Mainul HaqueAnaesthesia & Critical Care Research Group, University of Nottingham, Derby Road, Nottingham, NG7 2UH, UK. mainul.haque@nottingham.ac.uk.
Declan G BatesSchool of Engineering, University of Warwick, Library Road, Coventry, CV4 7AL, UK. D.Bates@warwick.ac.uk.
Jonathan G HardmanAnaesthesia & Critical Care Research Group, University of Nottingham, Derby Road, Nottingham, NG7 2UH, UK. J.Hardman@nottingham.ac.uk.
University of Nottingham · GBUniversity of Warwick · GB

Funding

Medical Research Council G1002017Medical Research Council MR/K019783Medical Research Council MR/K019783/1
6 · The paper itself

Abstract

introductionDirect comparison of the relative efficacy of different recruitment maneuvers (RMs) for patients with acute respiratory distress syndrome (ARDS) via clinical trials is difficult, due to the heterogeneity of patient populations and disease states, as well as a variety of practical issues. There is also significant uncertainty regarding the minimum values of positive end-expiratory pressure (PEEP) required to ensure maintenance of effective lung recruitment using RMs. We used patient-specific computational simulation to analyze how three different RMs act to improve physiological responses, and investigate how different levels of PEEP contribute to maintaining effective lung recruitment.

methodsWe conducted experiments on five 'virtual' ARDS patients using a computational simulator that reproduces static and dynamic features of a multivariable clinical dataset on the responses of individual ARDS patients to a range of ventilator inputs. Three recruitment maneuvers (sustained inflation (SI), maximal recruitment strategy (MRS) followed by a titrated PEEP, and prolonged recruitment maneuver (PRM)) were implemented and evaluated for a range of different pressure settings.

resultsAll maneuvers demonstrated improvements in gas exchange, but the extent and duration of improvement varied significantly, as did the observed mechanism of operation. Maintaining adequate post-RM levels of PEEP was seen to be crucial in avoiding cliff-edge type re-collapse of alveolar units for all maneuvers. For all five patients, the MRS exhibited the most prolonged improvement in oxygenation, and we found that a PEEP setting of 35 cm H2O with a fixed driving pressure of 15 cm H2O (above PEEP) was sufficient to achieve 95% recruitment. Subsequently, we found that PEEP titrated to a value of 16 cm H2O was able to maintain 95% recruitment in all five patients.

conclusionsThere appears to be significant scope for reducing the peak levels of PEEP originally specified in the MRS and hence to avoid exposing the lung to unnecessarily high pressures. More generally, our study highlights the huge potential of computer simulation to assist in evaluating the efficacy of different recruitment maneuvers, in understanding their modes of operation, in optimizing RMs for individual patients, and in supporting clinicians in the rational design of improved treatment strategies.

Indexed as

Computer SimulationModels, BiologicalHumansPositive-Pressure RespirationRespiration, ArtificialRespiratory Distress Syndrome

Identifiers

PMID25578295
PMCPMC4329196
OpenAlexW2071014982

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.