SARS-CoV-2 qRT-PCR Ct value distribution in Japan and possible utility of rapid antigen testing kit

  1. Yuta Takeda
  2. Masatoshi Mori
  3. Kazuya Omi

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Abstract

The exact pathology of COVID-19 remains mostly unclear, and accurate epidemiological understanding and rapid testing are crucial to overcome this disease. Several types of nucleic acid tests (NAT) have been used in Japan, but information about the viral RNA load, determined by Ct values, of the patients is limited due to the small number of patients tested in each clinical institution and lack of standardization of the testing kits. We have been performing the qRT-PCR tests established by NIID, and the mean Ct value distribution of 62 cases, which are deemed “first-visit” patients, among the total of 88 positive cases tested in a 4-day window of early April, was 24.9 with SD=5.45. Recently approved antigen testing kits were also used in the same samples (62 positives) along with 100 negative cases, and it revealed the positive predictive value of 80.6% and negative predictive value of 100%, with an overall agreement rate of 92.6%. These results indicate that a certain number of patients with lower Ct values, existed in Japan when SARS-CoV-2 virus started to spread. The newly approved rapid antigen testing kit will be a useful tool to identify such populations rapidly.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.16.20131243: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. ScreenIT

    SciScore for 10.1101/2020.06.16.20131243: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.RandomizationTo evaluate its utility in our company and performance, we have tested all 62 Initial ID samples and randomly selected 100 qRT-PCR negative specimens (162 cases total) using the rapid antigen testing kit.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.06.16.20131243 on medRxiv