Evidence map›Paper›PMID 35982716›Full record

ArticleFrontiers in medical technology2022

Personalised 3D printed respirators for healthcare workers during the COVID-19 pandemic.

Aidan D Roche, Alistair C McConnell, Karen Donaldson, Angus Lawson, Spring Tan, Kate Toft, Gillian Cairns, Alexandre Colle, Andrew A Coleman, Ken Stewart and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medical technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 42% 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, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
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

13 authors at 5 institutions in 1 country.

Aidan D RocheDeanery of Clinical Sciences, Queens Medical Research Institute, The University of Edinburgh, Edinburgh, United Kingdom.
Alistair C McConnellSchool of Engineering, Institute for Integrated Micro and Nano Systems, The University of Edinburgh, Edinburgh, United Kingdom.
Karen DonaldsonSchool of Engineering, Institute for Integrated Micro and Nano Systems, The University of Edinburgh, Edinburgh, United Kingdom.
Angus LawsonEdinburgh Medical School, The University of Edinburgh, Edinburgh, United Kingdom.
Spring TanRoslin Institute, The University of Edinburgh, Edinburgh, United Kingdom.
Kate ToftDepartment of Speech and Language Therapy, St John's Hospital, Livingston, United Kingdom.
Gillian CairnsDepartment of Speech and Language Therapy, Royal Hospital for Sick Children, Edinburgh, United Kingdom.
Alexandre ColleSchool of Engineering, Institute for Integrated Micro and Nano Systems, The University of Edinburgh, Edinburgh, United Kingdom.
Andrew A ColemanBayes Centre, University of Edinburgh, Edinburgh, United Kingdom.
Ken StewartDeanery of Clinical Sciences, Queens Medical Research Institute, The University of Edinburgh, Edinburgh, United Kingdom.
Paul DigardRoslin Institute, The University of Edinburgh, Edinburgh, United Kingdom.
John NorrieEdinburgh Clinical Trials Unit, The University of Edinburgh, Edinburgh, United Kingdom.
Adam A StokesSchool of Engineering, Institute for Integrated Micro and Nano Systems, The University of Edinburgh, Edinburgh, United Kingdom.
University of Edinburgh · GBRoslin Institute · GBRoyal Hospital for Children · GBSt John's Hospital · GBThe Queen's Medical Research Institute · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Widespread issues in respirator availability and fit have been rendered acutely apparent by the COVID-19 pandemic. This study sought to determine whether personalized 3D printed respirators provide adequate filtration and function for healthcare workers through a Randomized Controlled Trial (RCT). Fifty healthcare workers recruited within NHS Lothian, Scotland, underwent 3D facial scanning or 3D photographic reconstruction to produce 3D printed personalized respirators. The primary outcome measure was quantitative fit-testing to FFP3 standard. Secondary measures included respirator comfort, wearing experience, and function instrument (R-COMFI) for tolerability, Modified Rhyme Test (MRT) for intelligibility, and viral decontamination on respirator material. Of the 50 participants, 44 passed the fit test with the customized respirator, not significantly different from the 38 with the control (

Indexed as

3D printingCOVID-19facemaskfit-testingPPE

Identifiers

PMID35982716
PMCPMC9380470
OpenAlexW4289130846

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.