Evidence map›Paper›PMID 38002757›Full record

ArticleJournal of clinical medicine2023

Comparison of Manual versus Automated SARS-CoV-2 Rapid Antigen Testing in Asymptomatic Individuals.

David T Harris, Nicole Ingraham, Michael Badowski

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2023. 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 79% 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

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 at 1 institution in 1 country.

David T HarrisUniversity of Arizona Health Sciences Biorepository, Tucson, AZ 85724, USA.ORCID 0000-0001-9850-6234
Nicole IngrahamUniversity of Arizona Health Sciences Biorepository, Tucson, AZ 85724, USA.
Michael BadowskiUniversity of Arizona Health Sciences Biorepository, Tucson, AZ 85724, USA.
University of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 pandemic has infected more than 770 M people and killed more than 6.9 M persons worldwide. In the USA, as of August 2023, it has infected more than 103 M people while causing more than 1.1 M deaths. During a pandemic, it is necessary to rapidly identify those individuals infected with the virus so that disease transmission can be stopped. We examined the sensitivity of the Quidel Rapid Antigen test on the manual Sofia 2 platform and the Beckman-Coulter antigen test on the automated DxI-800 system for use in screening asymptomatic individuals at the University of Arizona from March through May 2021. A total of 378 asymptomatic subjects along with 176 validation sets of samples in 23 independent experiments were assessed in side-by-side antigen testing using both assays. Nasal swabs and saliva were used as viral sources. Manual testing (Quidel) was compared with automated testing (Beckman) methods for cost and efficiency. Limit dilution of viral antigen spiked samples was performed to determine sensitivity to antigen load by the tests. The results between the two tests were found to be concordant. Both tests were comparable in terms of detecting low numbers of positive subjects in the asymptomatic population. A concordance of 98% was observed between the two tests. Experiments also demonstrated that saliva specimens were an acceptable viral source and produced comparable results for each test. Overall, the two methods were interchangeable.

Indexed as

asymptomaticCOVID-19diagnosticsrapid antigen testingSARS-CoV-2

Identifiers

PMID38002757
PMCPMC10672191
OpenAlexW4388775205

What OpenQuestion holds

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LicenceCC BY
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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.