Evidence map›Paper›PMID 34649631›Full record

ArticleDisaster medicine and public health preparedness2022

Use of Breath Analysis for Diagnosing COVID-19: Opportunities, Challenges, and Considerations for Future Pandemic Responses.

Mustafa Abumeeiz, Lauren Elliott, Phillip Olla

Open access · greenAbstract read
In one paragraph

Article in Disaster medicine and public health preparedness, 2022. 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
0.7field-weighted citation impact, top 34% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

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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.

Mustafa AbumeeizAudacia Bioscience, Windsor, Ontario, Canada.
Lauren ElliottAudacia Bioscience, Windsor, Ontario, Canada.ORCID 0000-0003-1120-1492
Phillip OllaAudacia Bioscience, Windsor, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the coronavirus disease 2019 (COVID-19) pandemic, there is currently a need for accurate, rapid, and easy-to-administer diagnostic tools to help communities manage local outbreaks and assess the spread of disease. The use of artificial intelligence within the domain of breath analysis techniques has shown to have potential in diagnosing a variety of diseases, such as cancer and lung disease, by analyzing volatile organic compounds (VOCs) in exhaled breath. This combined with their rapid, easy-to-use, and noninvasive nature makes them a good candidate for use in diagnosing COVID-19 in large scale public health operations. However, there remains issues with their implementation when it comes to the infrastructure currently available to support their use on a broad scale. This includes issues of standardization, and whether or not a characteristic VOC pattern can be identified for COVID-19. Despite these difficulties, breathalyzers offer potential to assist in pandemic responses and their use should be investigated.

Indexed as

COVID-19Volatile Organic CompoundsArtificial IntelligenceBreath TestsExhalationHumansPandemicsVolatile Organic CompoundsCOVID-19efficacypandemicpublic healthtechnologyvolatile organic compounds

Identifiers

PMID34649631
PMCPMC8576132
OpenAlexW3206414684

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.