Efficacy and Safety of Ayurveda Intervention (AYUSH 64) as add-on therapy for patients with COVID-19 infections – An open labelled, Parallel Group, Randomized controlled clinical trial

  1. Pankaj bhardwaj
  2. Pawan Kumar Godatwar
  3. Jaykaran Charan
  4. Sanjeev Sharma
  5. Shazia Shafi
  6. Nishant Chauhan
  7. Pratibha Vyas
  8. Naveen Dutt
  9. Naresh Midha
  10. Ramniwas Jalandra
  11. Meenakshi Sharma
  12. Vijaya Lakshmi Nag
  13. Suman Sharma
  14. Sarvesh Kumar Singh
  15. Praveen Sharma
  16. Sanjeev Misra

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Abstract

The authors have withdrawn this manuscript because they found a serious issue in data-analysis which leads to wrong interpretation of the results. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

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  1. Version published to 10.1101/2021.08.10.21261836v3 on medRxiv
  2. Version published to 10.1101/2021.08.10.21261836v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.08.10.21261836: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Subjects aged 18 to 60 years, who tested RT-PCR positive for COVID-19 and were categorized under stage I- mild (early infection), willing to take medicines orally and to provide signed informed consent were included in the study.
    IACUC: Study procedure: This study was started after registering trial in Clinical Trial Registry of India (CTRI) (CTRI/2020/06/026002) and getting permission from the Institutional Ethics Committee (AIIMS/IEC/2020-21/3036).
    Sex as a biological variablePregnant, Lactating women, patients with CKD (chronic kidney disease), and those not willing to participate were excluded from the study.
    RandomizationBased on the computer based randomized sequence 30 subjects were enrolled in group 1 (intervention arm) and 30 in group 2 (control arm).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistics for Windows, version 23 (SPSS Inc., Chicago, IL, USA) was used for the analysis.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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.

    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.

  4. Version published to 10.1101/2021.08.10.21261836v1 on medRxiv