Evidence map›Paper›PMID 33519790›Full record

ArticleFrontiers in microbiology2020

Development of an Automated Chemiluminescence Assay System for Quantitative Measurement of Multiple Anti-SARS-CoV-2 Antibodies.

Sousuke Kubo, Norihisa Ohtake, Kei Miyakawa, Sundararaj Stanleyraj Jeremiah, Yutaro Yamaoka, Kota Murohashi, Eri Hagiwara, Takahiro Mihara, Atsushi Goto, Etsuko Yamazaki and 4 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Article
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  8. Review
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  11. Metal Organic Frameworks as Biosensing Materials for COVID-19.Cellular and molecular bioengineering · 2021
    Review
  12. Review
  13. Article
  14. Development of a cell-free protein synthesis system for practical use.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2021
    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

14 authors.

Sousuke KuboDepartment of Microbiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Norihisa OhtakeBioscience Division, Reagent Development Department, Tosoh Corporation, Kanagawa, Japan.
Kei MiyakawaDepartment of Microbiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Sundararaj Stanleyraj JeremiahDepartment of Microbiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Yutaro YamaokaDepartment of Microbiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Kota MurohashiDepartment of Pulmonology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Eri HagiwaraDepartment of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, Yokohama, Japan.
Takahiro MiharaDepartment of Health Data Science, Yokohama City University Graduate School of Data Science, Yokohama, Japan.
Atsushi GotoDepartment of Health Data Science, Yokohama City University Graduate School of Data Science, Yokohama, Japan.
Etsuko YamazakiClinical Laboratory Department, Yokohama City University Hospital, Yokohama, Japan.
Takashi OguraDepartment of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, Yokohama, Japan.
Takeshi KanekoDepartment of Pulmonology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.
Takeharu YamanakaDepartment of Health Data Science, Yokohama City University Graduate School of Data Science, Yokohama, Japan.
Akihide RyoDepartment of Microbiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSerological tests for COVID-19 have been instrumental in studying the epidemiology of the disease. However, the performance of the currently available tests is plagued by the problem of variability. We have developed a high-throughput serological test capable of simultaneously detecting total immunoglobulins (Ig) and immunoglobulin G (IgG) against nucleocapsid protein (NP) and spike protein (SP) and report its performance in detecting COVID-19 in clinical samples.

methodsWe designed and prepared reagents for measuring NP-IgG, NP-Total Ig, SP-IgG, and SP-Total Ig (using N-terminally truncated NP (ΔN-NP) or receptor-binding domain (RBD) antigen) dedicated automated chemiluminescent enzyme immunoassay analyzer AIA-CL1200. After determining the basal thresholds based on 17 sera obtained from confirmed COVID-19 patients and 600 negative sera, the clinical validity of the assay was evaluated using independent 202 positive samples and 1,000 negative samples from healthy donors.

resultsAll of the four test parameters showed 100% specificity individually (1,000/1,000; 95%CI, 99.63-100). The sensitivity of the assay increased proportionally to the elapsed time from symptoms onset, and all the tests achieved 100% sensitivity (153/153; 95%CI, 97.63-100) after 13 days from symptoms onset. NP-Total Ig was the earliest to attain maximal sensitivity among the other antibodies tested.

conclusionOur newly developed serological testing exhibited 100% sensitivity and specificity after 13 days from symptoms onset. Hence, it could be used as a reliable method for accurate detection of COVID-19 patients and to evaluate seroprevalence and possibly for surrogate assessment of herd immunity.

Indexed as

automated chemiluminescent enzyme immunoassayCOVID-19multiple antibody measurementsquantitative serological testSARS-CoV-2

Identifiers

PMID33519790
PMCPMC7843449

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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.