A large-scale clinical validation study using nCapp cloud plus terminal by frontline doctors for the rapid diagnosis of COVID-19 and COVID-19 pneumonia in China

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.08.07.20163402: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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: We detected the following sentences addressing limitations in the study:
    One limitation of this study is that the uploaded cases were mainly moderate-to-severe COVID-19 cases, which leads to restrictions on the application of nCapp for mild patients. In addition, WeChat is not widely used in European or American countries, despite its popularity as a social media cloud platform in China and its emerging application for medical purposes. To address this issue, one approach would be to popularize WeChat, or to develop tools on a similar platform such as WhatsApp for the diagnosis and treatment of COVID-19, in compliance with HIPAA regulations to protect patient data privacy.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04275947RecruitingThe COVID-19 Mobile Health Study (CMHS)


    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.