Evidence map›Paper›PMID 35729011›Full record

ArticleBritish journal of anaesthesia2022

Simulation to minimise patient self-inflicted lung injury: are we almost there?

Vasiliki Tsolaki, George E Zakynthinos

Open access · greenAbstract readEditorialComment
PubMed Full text at PMC Publisher
In one paragraph

Article in British journal of anaesthesia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 87% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Vasiliki TsolakiDepartment of Intensive Care Medicine, General University of Larissa, University of Thessaly, Faculty of Medicine, Larissa, Thessaly, Greece. Electronic address: vasotsolaki@yahoo.com.
George E ZakynthinosDepartment of Intensive Care Medicine, General University of Larissa, University of Thessaly, Faculty of Medicine, Larissa, Thessaly, Greece.
University of Thessaly · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational modelling has been used to enlighten pathophysiological issues in patients with acute respiratory distress syndrome (ARDS) using a sophisticated, integrated cardiopulmonary model. COVID-19 ARDS is a pathophysiologically distinct entity characterised by dissociation between impairment in gas exchange and respiratory system mechanics, especially in the early stages of ARDS. Weaver and colleagues used computational modelling to elucidate factors contributing to generation of patient self-inflicted lung injury, and evaluated the effects of various spontaneous respiratory efforts with different oxygenation and ventilatory support modes. Their findings indicate that mechanical forces generated in the lung parenchyma are only counterbalanced when the respiratory support mode reduces the intensity of respiratory efforts.

Indexed as

COVID-19Lung InjuryRespiratory Distress SyndromeComputer SimulationHumansLungPositive-Pressure RespirationRespiration, ArtificialRespiratory MechanicsARDScomputational modellingCOVID-19lung injurypatient self-inflicted lung injurysimulation

Identifiers

PMID35729011
PMCPMC9551385
OpenAlexW4283078149

What OpenQuestion holds

Textmetadata
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.