Evidence map›Paper›PMID 24581274›Full record

ArticleBMC pulmonary medicine2014

Visualisation of time-varying respiratory system elastance in experimental ARDS animal models.

Erwin J van Drunen, Yeong Shiong Chiew, Christopher Pretty, Geoffrey M Shaw, Bernard Lambermont, Nathalie Janssen, J Geoffrey Chase, Thomas Desaive

Open access · goldAbstract read
In one paragraph

Article in BMC pulmonary medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.6field-weighted citation impact, top 7% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 45 citations in OpenAlex.

  1. Non-invasive over-distension measurements: data driven vs model-based.Journal of clinical monitoring and computing · 2023
    Article
  2. Article
  3. Article
  4. Article
  5. Quantifying neonatal patient effort using non-invasive model-based methods.Medical & biological engineering & computing · 2022
    Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
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 3 institutions in 2 countries.

Erwin J van Drunen
Yeong Shiong Chiew
Christopher Pretty
Geoffrey M Shaw
Bernard Lambermont
Nathalie Janssen
J Geoffrey Chase
Thomas DesaiveUniversity of Liège, Liège, Belgium. tdesaive@ulg.ac.be.
University of Canterbury · NZChristchurch Hospital · NZUniversity of Liège · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics. Model-based estimation of respiratory mechanics characterising patient-specific condition and response to treatment may be used to guide mechanical ventilation (MV). This study presents a model-based approach to monitor time-varying patient-ventilator interaction to guide positive end expiratory pressure (PEEP) selection.

methodsThe single compartment lung model was extended to monitor dynamic time-varying respiratory system elastance, Edrs, within each breathing cycle. Two separate animal models were considered, each consisting of three fully sedated pure pietrain piglets (oleic acid ARDS and lavage ARDS). A staircase recruitment manoeuvre was performed on all six subjects after ARDS was induced. The Edrs was mapped across each breathing cycle for each subject.

resultsSix time-varying, breath-specific Edrs maps were generated, one for each subject. Each Edrs map shows the subject-specific response to mechanical ventilation (MV), indicating the need for a model-based approach to guide MV. This method of visualisation provides high resolution insight into the time-varying respiratory mechanics to aid clinical decision making. Using the Edrs maps, minimal time-varying elastance was identified, which can be used to select optimal PEEP.

conclusionsReal-time continuous monitoring of in-breath mechanics provides further insight into lung physiology. Therefore, there is potential for this new monitoring method to aid clinicians in guiding MV treatment. These are the first such maps generated and they thus show unique results in high resolution. The model is limited to a constant respiratory resistance throughout inspiration which may not be valid in some cases. However, trends match clinical expectation and the results highlight both the subject-specificity of the model, as well as significant inter-subject variability.

Indexed as

Respiratory MechanicsAnimalsDisease Models, AnimalRespiratory Distress SyndromeSwineTime Factors

Identifiers

PMID24581274
PMCPMC4016000
OpenAlexW2130207642

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.