Previous COVID-19 infection, but not Long-COVID, is associated with increased adverse events following BNT162b2/Pfizer vaccination

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Abstract

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  1. SciScore for 10.1101/2021.04.15.21252192: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study was approved by Cambridge East Research Ethics Committee.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Respondents who had permitted laboratory results to be accessed (SARS-CoV-2 PCR and antibody), formed a subgroup for sensitivity analysis.
    antibody
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analysis was carried out using JASP v0.14.1.0.
    JASP
    suggested: (JASP, RRID:SCR_015823)

    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:
    Our study has several limitations. Firstly, some non-responder bias13 is likely, with 27% of participants reporting previous COVID-19. This is slightly higher than in UK healthcare workers.15 Nevertheless, the sample was broadly representative of UK healthcare employees and likely generalizable. Secondly, information on AEs was gathered via self-reported questionnaires, and hence subjective. Thirdly, PCR and antibody results were self-reported. We addressed this via a sensitivity analysis on a subset of participants with laboratory data available, which mostly confirmed the findings in the entire sample. Finally, the numbers with Long-COVID were relative small for comparison. In conclusion, this large study shows an association of previous COVID-19 with increased AEs and will help those with previous COVID-19 infection understand better what to expect following vaccination.

    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.