COVID-19 Living Overview of Evidence repository is highly comprehensive and can be used as a single source for COVID-19 studies

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Abstract

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  1. SciScore for 10.1101/2021.09.21.21263849: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationAs randomised trials are particularly relevant for decision-making, we also run a regular search for randomised trials on Twitter using the terms #COVID19 OR #COVID-19 OR #COVID_19 OR #COVID randomized OR randomised, and scan relevant scientific conferences, press release websites and the websites of the main trials or companies relevant to COVID-19.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The sources include PubMed, EMBASE, CINAHL (the Cumulative Index to Nursing and Allied Health Literature), PsycINFO, LILACS (Latin American & Caribbean Health Sciences Literature), Wanfang Database, CBM (Chinese Biomedical Literature Database), CNKI (Chinese National Knowledge Infrastructure), VIP (Chinese Scientific Journal Database), IRIS (WHO Institutional Repository for Information Sharing), IRIS PAHO (PAHO Institutional Repository for Information Sharing), IBECS (Spanish Bibliographic Index on Health Sciences), Microsoft Academic, ICTRP Search Portal, Clinicaltrials.gov, ISRCTN registry, Chinese Clinical Trial Registry, IRCT (Iranian Registry of Clinical Trials), EU Clinical Trials Register, Japan NIPH Clinical Trials Search, JPRN (Japan Primary Registries Network - includes JapicCTI, JMACCT CTR, jRCT, UMIN CTR), CRiS (Clinical Research Information Service), ANZCTR (Australian New Zealand Clinical Trials Registry), ReBec (Brazilian Clinical Trials Registry), CTRI (Clinical Trials Registry - India), RPCEC (Cuban Public Registry of Clinical Trials), DRKS (German Clinical Trials Register), LBCTR (Lebanese Clinical Trials Registry), TCTR (Thai Clinical Trials Registry), NTR (The Netherlands National Trial Register), PACTR (Pan African Clinical Trial Registry), REPEC (Peruvian Clinical Trial Registry), SLCTR (Sri Lanka Clinical Trials Registry), MedRxiv, BioRxiv, SSRN Preprints, Research Square, ChinaXiv and SciELO Preprints.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    PsycINFO
    suggested: (PsycINFO, RRID:SCR_014799)
    BioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)

    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 our study is that a sample obtained by the relative recall method might not be representative of the total number of existing studies [11]. Considering the high level of standardisation of systematic reviews it is possible they all cover much the same territory. An evaluation against a sample derived from a manual review of journals and other sources might provide a more reliable estimate [19]. However, this approach may not be suitable in the context of the deluge of scientific information about COVID-19. Another limitation of our evaluation is the scope of the assessment. We addressed only primary studies and not the other types of scientific articles that are contained in the COVID-19 L·OVE repository, which includes any type of scientific article. Considering the inclusive nature of the methods used to maintain the COVID-19 L·OVE repository, we can expect similar results for the other types of articles, but a formal evaluation would provide a definitive answer. Our study is not designed to assess the specificity of the repository nor any of the components of the COVID-19 classification platform. We believe the latter has enormous potential to increase the reliability of search processes and to reduce the amount of work involved. However, it is yet to be tested. Implications: Accessing all the available studies for a particular topic is key to avoiding being misled by research [20]. Unfortunately, substantial time and resources are needed to comprehensive...

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.