Exploring alternative medicine options for the prevention or treatment of coronavirus disease 2019 (COVID-19)- A systematic scoping review

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Abstract

Background: Coronavirus disease 2019 (COVID-19) is caused by coronavirus 2 (SARS-CoV-2). Symptoms include fever, cough, shortness of breath, muscle pain, pneumonia, and multi-organ failure. The infection spreads from one person to another via respiratory droplets. Alternative medicine (AMs) viz., Ayurveda, Homeopathy, Unani, and Traditional Chinese Medicine (TCM), are being promoted for the prevention of COVID-19. The aim of this systematic scoping review was to identify and summarize the scientific evidences promoting the use of AMs for the prevention of COVID-19. Methods: A comprehensive search of electronic search engines (PubMed and Web of Science) was performed. In addition, freewheeling searches of the government health ministries and government websites was done to retrieve the available information. Records available until 12th March 2020 were considered. Reports proposing the use of AMs for prevention or treatment of COVID-19 across all countries were included. Screening (primary and secondary) of the records and data extraction from the eligible studies were done by a single reviewer followed by a random quality check (10%) by the second reviewer. Results: Overall, 8 records (7 from China and 1 from India) exploring the use of AMs for the prevention or treatment of COVID-19 were identified. Different medicines were explored by different AM systems. Conclusions: Several AMs options are proposed for the prevention or treatment of COVID-19. However, their efficacy and safety still needs scientific validation through rigorous randomized controlled trials. This review may help inform decisions about the importance of research and development of AMs for COVID-19 prevention and treatment.

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  1. SciScore for 10.1101/2020.05.14.20101352: (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

    Software and Algorithms
    SentencesResources
    Briefly, electronic search engines (PubMed and Web of Science) were screened from the inception database to 12th of March 2020.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    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.