Evidence map›Paper›PMID 36268504›Full record

ArticleEuropean journal of mechanics. B, Fluids

Computational design and experimental analysis of a novel visor for COVID-19 patients receiving high-flow nasal oxygen therapy.

Masooma Ijaz, Sorcha Ni Fhrighil, Rory Brett, Jack Connolly, Alan Conneely, Gerard O'Connor, Martin O'Halloran, Sajjad Yousefian

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European journal of mechanics. B, Fluids. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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 2 institutions in 1 country.

Masooma IjazMechanical Engineering, College of Engineering and Informatics, National University of Ireland, Galway, Ireland.
Sorcha Ni FhrighilMechanical Engineering, College of Engineering and Informatics, National University of Ireland, Galway, Ireland.
Rory BrettMechanical Engineering, College of Engineering and Informatics, National University of Ireland, Galway, Ireland.
Jack ConnollyBioInnovate Ireland, National University of Ireland, Galway, Ireland.
Alan ConneelyNational Centre for Laser Applications, School of Physics, College of Science and Engineering National University of Ireland, Galway, Ireland.
Gerard O'ConnorTranslational Medical Device Lab, Lambe Institute for Translational Research & HRB Clinical Research Facility, University Hospital Galway, Galway, Ireland.
Martin O'HalloranTranslational Medical Device Lab, Lambe Institute for Translational Research & HRB Clinical Research Facility, University Hospital Galway, Galway, Ireland.
Sajjad YousefianMechanical Engineering, College of Engineering and Informatics, National University of Ireland, Galway, Ireland.
Ollscoil na Gaillimhe – University of Galway · IEUniversity Hospital Galway · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Covid-19 global pandemic has reshaped the requirements of healthcare sectors worldwide. Following the exposure risks associated with Covid-19, this paper aims to design, optimise, and validate a wearable medical device that reduces the risk of transmission of contagious droplets from infected patients in a hospital setting. This study specifically focuses on those receiving high-flow nasal oxygen therapy. The design process consisted of optimising the geometry of the visor to ensure that the maximum possible percentage of harmful droplets exhaled by the patient can be successfully captured by a vacuum tube attached to the visor. This has been completed by deriving a number of concept designs and assessing their effectiveness, based on numerical analysis, computational fluid dynamics (CFD) simulations and experimental testing. The CFD results are validated using various experimental methods such as Schlieren imaging, particle measurement testing and laser sheet visualisation. Droplet capturing efficiency of the visor was measured through CFD and validated through experimental particle measurement testing. The results presented a 5% deviation between CFD and experimental results. Also, the modifications based on the validated CFD results improved the visor effectiveness by 47% and 38% for breathing and coughing events, respectively.

Indexed as

Computational fluid dynamics (CFD)COVID-19High flow nasal oxygen therapy (HFNOT)Particle extraction visorSchlieren imaging

Identifiers

PMID36268504
PMCPMC9562623
OpenAlexW4298148345

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.