Evidence map›Paper›PMID 36017468›Full record

ArticleTheScientificWorldJournal2022

Diagnostic Performance of Three ELISAs for Detection of Antibodies against SARS-CoV-2 in Human Samples.

Cássio Meira, Dahara Silva, Ivanilson Santos, Breno Barreto, Vinícius Rocha, Emanuelle Santos, Bruna Dos Reis, Afrânio Evangelista, Ricardo Ribeiro Dos Santos, Bruna Machado and 3 more

Open access · goldAbstract read
In one paragraph

Article in TheScientificWorldJournal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

13 authors at 3 institutions in 1 country.

Cássio MeiraSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0002-7578-3615
Dahara SilvaSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.
Ivanilson SantosGonçalo Moniz Institute Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil.ORCID https://orcid.org/0000-0002-2331-6150
Breno BarretoGonçalo Moniz Institute Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil.ORCID https://orcid.org/0000-0002-9897-2443
Vinícius RochaSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0002-5309-5950
Emanuelle SantosSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0002-5213-8197
Bruna Dos ReisGonçalo Moniz Institute Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil.ORCID https://orcid.org/0000-0002-3863-7483
Afrânio EvangelistaSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0001-8011-4128
Ricardo Ribeiro Dos SantosSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0001-9216-0498
Bruna MachadoSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0003-1655-0325
Guilherme RibeiroGonçalo Moniz Institute Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil.
Roberto BadaróSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0002-2861-5061
Milena SoaresSENAI Institute of Innovation in Health Advanced Systems (CIMATEC ISI SAS), University Center SENAI/CIMATEC, Salvador, Brazil.ORCID https://orcid.org/0000-0001-7549-2992
Serviço Nacional de Aprendizagem Industrial · BRFundação Oswaldo Cruz · BRUniversidade Federal da Bahia · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that causes coronavirus disease 2019 (COVID-19) is a disease with a high rate of transmission. Serological tests are important to perform surveys and to determine the immunological status of the population. Based on this, we evaluated three enzyme-linked immunoassays (ELISAs) using different antigens from SARS-CoV-2 in a cohort of 161 patients. The performance of the ELISA developed for immunoglobulin G (IgG) measurement against SARS-CoV-2 was evaluated based on sensitivity, specificity, and accuracy. We found specificities of 0.98, 0.98, and 0.99 and sensitivities of 0.99, 0.91, and 0.87 for the nucleocapsid (N) protein, spike protein, and receptor binding domain (RBD) fraction, respectively. The accuracy assessment indicated the N protein (accuracy = 0.98) as the antigen most likely to give a correct diagnosis. Overall, the antibody responses were present for all three proteins in subjects with confirmed SARS-CoV-2 infections, showing a similar pattern of antibody production for different antigens. In summary, these highly sensitive and specific ELISAs, with a more competitive price, appear to be a valid approach for the serodiagnosis of COVID-19.

Indexed as

COVID-19SARS-CoV-2Antibodies, ViralCOVID-19 TestingEnzyme-Linked Immunosorbent AssayHumansSensitivity and SpecificitySerologic TestsSpike Glycoprotein, CoronavirusAntibodies, ViralSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2

Identifiers

PMID36017468
PMCPMC9398874
OpenAlexW4292014167

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.