Evidence map›Paper›PMID 33920222›Full record

ArticleViruses2021

SARS-CoV-2 Serum Neutralization Assay: A Traditional Tool for a Brand-New Virus.

Giulia Matusali, Francesca Colavita, Daniele Lapa, Silvia Meschi, Licia Bordi, Pierluca Piselli, Roberta Gagliardini, Angela Corpolongo, Emanuele Nicastri, Andrea Antinori and 4 more

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

47 citing papers in PubMed, 68 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

14 authors at 1 institution in 2 countries.

Giulia MatusaliNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.ORCID 0000-0002-2948-4243
Francesca ColavitaNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.ORCID 0000-0003-0640-8667
Daniele LapaNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.
Silvia MeschiNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.
Licia BordiNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.
Pierluca PiselliNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.ORCID 0000-0002-7342-0263
Roberta GagliardiniNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.
Angela CorpolongoNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.ORCID 0000-0001-6235-3934
Emanuele NicastriNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.ORCID 0000-0002-5606-8712
Andrea AntinoriNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.
Giuseppe IppolitoNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.ORCID 0000-0002-1076-2979
Maria Rosaria CapobianchiNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.
Concetta CastillettiNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.ORCID 0000-0001-9819-236X
Inmi Covid-Laboratory TeamNational Institute for Infectious Diseases "L. Spallanzani" IRCCS, Via Portuense 292, 00149 Rome, Italy.
Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2 serum neutralization assay represents the gold standard for assessing antibody-mediated protection in naturally infected and vaccinated individuals. In the present study, 662 serum samples collected from February 2020 to January 2021 from acute and convalescent COVID-19 patients were tested to determine neutralizing antibody (NAb) titers using a microneutralization test (MNT) for live SARS-CoV-2. Moreover, anti-SARS-CoV-2 IgG, IgA, and IgM directed against different viral antigens were measured by high-throughput automated platforms. We observed higher levels of NAbs in elderly (>60 years old) individuals and in patients presenting acute respiratory distress syndrome. SARS-CoV-2 NAbs develop as soon as five days from symptom onset and, despite a decline after the second month, persist for over 11 months, showing variable dynamics. Through correlation and receiver operating characteristic (ROC) curve analysis, we set up a testing algorithm, suitable for the laboratory workload, by establishing an optimal cutoff value of anti-SARS-CoV-2 IgG for convalescent plasma donors to exclude from MNT samples foreseen to have low/negative NAb titers and ineligible for plasma donation. Overall, MNT, although cumbersome and not suitable for routine testing of large sample sizes, remains the reference tool for the assessment of antibody-mediated immunity after SARS-CoV-2 infection. Smart testing algorithms may optimize the laboratory workflow to monitor antibody-mediated protection in COVID-19 patients, plasma donors, and vaccinated individuals.

Indexed as

AdultAlgorithmsAntibodies, NeutralizingAntibodies, ViralCOVID-19COVID-19 Serological TestingFemaleHumansImmunoglobulin GKineticsMaleMiddle AgedNeutralization TestsROC CurveSARS-CoV-2Antibodies, NeutralizingAntibodies, ViralImmunoglobulin Gneutralizing antibodiesprotective immunitySARS-CoV-2serology

Identifiers

PMID33920222
PMCPMC8069482
OpenAlexW3153284520

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.