Safe and effective pool testing for SARS-CoV-2 detection

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Abstract

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  1. SciScore for 10.1101/2021.04.08.20205781: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the Institutional Review Board (Ethics Committee) of the Medical Faculty, University Hospital Cologne, Germany (ethical vote no. 20-1638).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    GraphPadPrism 7.0 (GraphPad Software, Inc.) was used for statistical analysis.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Figures were created using Adobe Illustrator 18.1
    Adobe Illustrator
    suggested: (Adobe Illustrator, RRID:SCR_010279)

    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:
    In our study, different operators performed specimen collection, which could be a limitation of the data, as analyzed by Basso and colleagues. Two different operators collected 70 swabs each and a high variability of test results was observed [38]. This effect should not be underestimated. We developed a feasible pooling procedure that can readily be implemented in diagnostic routines. The preparation for pool testing contained besides extensive technical investigations, also changes in the laboratory logistics and adaptions of the laboratory software. The data communicated here will contribute to the process of finding and implementing a consensus pool testing strategy enabling larger test capacities to effectively combat the SARS-CoV-2 pandemic.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    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.