Evidence map›Paper›PMID 28952566›Full record

ArticleBioengineering (Basel, Switzerland)2016

Transient Mechanical Response of Lung Airway Tissue during Mechanical Ventilation.

Israr Bin Muhammad Ibrahim, Parya Aghasafari, Ramana M Pidaparti

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Evaluation of Ventilation-Induced Lung Inflammation Through Multi-Scale Simulations.IEEE journal of translational engineering in health and medicine · 2018
    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

3 authors.

Israr Bin Muhammad IbrahimGraduate Student, College of Engineering, University of Georgia, 597 DW Brooks Drive, Athens, GA 30602, USA. israr@uga.edu.
Parya AghasafariGraduate Student, College of Engineering, University of Georgia, 597 DW Brooks Drive, Athens, GA 30602, USA. parya.aghasafari@uga.edu.
Ramana M PidapartiCollege of Engineering, University of Georgia, 132A Paul D. Coverdell Center, Athens, GA 30602, USA. rmparti@uga.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with acute lung injury, airway and other pulmonary diseases often require Mechanical Ventilation (MV). Knowledge of the stress/strain environment in lung airway tissues is very important in order to avoid lung injuries for patients undergoing MV. Airway tissue strains responsible for stressing the lung's fiber network and rupturing the lung due to compliant airways are very difficult to measure experimentally. Multi-level modeling is adopted to investigate the transient mechanical response of the tissue under MV. First, airflow through a lung airway bifurcation (Generation 4-6) is modeled using Computational Fluid Dynamics (CFD) to obtain air pressure during 2 seconds of MV breathing. Next, the transient air pressure was used in structural analysis to obtain mechanical strain experienced by the airway tissue wall. Structural analysis showed that airway tissue from Generation 5 in one bifurcation can stretch eight times that of airway tissue of the same generation number but with different bifurcation. The results suggest sensitivity of load to geometrical features. Furthermore, the results of strain levels obtained from the tissue analysis are very important because these strains at the cellular-level can create inflammatory responses, thus damaging the airway tissues.

Indexed as

finite element analysislung airwaymechanical strainsmechanical ventilation

Identifiers

PMID28952566
PMCPMC5597162

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.