Evidence map›Paper›PMID 36754135›Full record

ArticleAnalytical biochemistry2023

Diagnostic performance of a novel antigen-capture ELISA for the detection of SARS-CoV-2.

Hamidreza Yadegari, Mehdi Mohammadi, Faezeh Maghsood, Ahmad Ghorbani, Tannaz Bahadori, Forough Golsaz-Shirazi, Amir-Hassan Zarnani, Vahid Salimi, Mahmood Jeddi-Tehrani, Mohammad Mehdi Amiri and 1 more

Open access · greenAbstract read
In one paragraph

Article in Analytical biochemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

8 citing papers in PubMed, 16 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

11 authors at 2 institutions in 1 country.

Hamidreza YadegariDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mehdi MohammadiDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Faezeh MaghsoodDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Ahmad GhorbaniDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Tannaz BahadoriDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Forough Golsaz-ShiraziDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Amir-Hassan ZarnaniDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Vahid SalimiDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mahmood Jeddi-TehraniMonoclonal Antibody Research Center, Avicenna Research Institute, Academic Center for Education, Culture and Research (ACECR), Tehran, Iran.
Mohammad Mehdi AmiriDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: m_amiri@tums.ac.ir.
Fazel ShokriDepartment of Immunology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: fshokri@tums.ac.ir.
Tehran University of Medical Sciences · IRAcademic Center for Education, Culture and Research · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsThe coronavirus disease 2019 (COVID-19) pandemic is a serious health problem worldwide. Early virus detection is essential for disease control and management. Viral antigen detection by ELISA is a cost-effective, rapid, and accurate antigen diagnostic assay which could facilitate early viral detection.

methodAn antigen-capture sandwich ELISA was developed using novel nucleocapsid (NP)-specific mouse monoclonal antibodies (MAbs). The clinical performance of the assay was assessed using 403 positive and 150 negative respiratory samples collected during different SARS-CoV-2 variants outbreaks in Iran.

resultsThe limit of detection of our ELISA assay was found to be 43.3 pg/ml for recombinant NP. The overall sensitivity and specificity of this assay were 70.72% (95% CI: 66.01-75.12) and 100% (95% CI: 97.57-100), respectively, regardless of Ct values and SARS-CoV-2 variants. There was no significant difference in our assay sensitivity for the detection of Omicron subvariants compared to Delta variant. Assay sensitivity for the BA.5 Omicron subvariant was calculated as 91.89% (95% CI: 85.17-96.23) for samples with Ct values < 25 and 82.70% (95% CI: 75.19-88.71) for samples with Ct values < 30.

conclusionOur newly developed ELISA method is reasonably sensitive and highly specific for detection of SARS-CoV-2 regardless of the variants and subvariants of the virus.

Indexed as

COVID-19SARS-CoV-2AnimalsAntibodies, MonoclonalAntibodies, ViralCOVID-19 TestingEnzyme-Linked Immunosorbent AssayMiceSensitivity and SpecificityAntibodies, MonoclonalAntibodies, ViralCOVID-19Monoclonal antibodyNucleocapsidSandwich ELISASARS-CoV-2

Identifiers

PMID36754135
PMCPMC9902293
OpenAlexW4319442792

What OpenQuestion holds

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Registered trials

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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.