Efficacy and Safety of Guduchi Ghan Vati in the Management of Asymptomatic COVID-19 Infection: An Open Label Feasibility Study

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Abstract

Background

Guduchi Ghan Vati (aqueous extract of Tinospora cordifolia ) is an essential herbal plant in Indian traditional medicine (Ayurveda) that is well documented as an immunomodulator and antimicrobial agent. A recent in silico study found the therapeutic efficacy of Guduchi against SARS-CoV-2. Based on available evidence, we conducted a feasibility study of the safety and efficacy of Guduchi Ghan Vati in asymptomatic patients with covid-19.

Patients and methods

An open label, feasibility trial was conducted on 46 patients in the hospital setting. A single-arm study with no control group and blinding was executed in Jodhpur, Rajasthan, India. All patients orally received 2 tablets (1000 mg) twice daily for 2 weeks. Clinical parameters were collected at baseline, day 3, day 7 and day 14. Patients were continuously monitored for side effects and adverse reactions during the study period..

Results

Out of 46 asymptomatic patients included in the study, 40 completed the 14-day follow-up period. None developed any Covid-19 symptoms after admission to the hospital. On day 3 post-treatment, viral clearance was reported in 16 (32.5%) patients. By the end of D-7, 38 (95%) patients had viral load disappearance. Follow-up at D-14 showed that all participants tested negative.

Conclusion

In adult patients with asymptomatic Covid-19, Gudhuchi Ghan Vati could be effective. Randomized controlled trials with larger sample sizes in patients with Covid-19 are urgently needed to confirm the definite benefit with Ayurveda.

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  1. SciScore for 10.1101/2020.09.20.20198515: (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, who independently reviewed the safety of the drug administered.
    Consent: Written informed consent was obtained from each participant.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The research assistant then entered confirmed data, masking the patient identifications and any contact details, into the Medcalc statistical software database for statistical analyses.
    Medcalc
    suggested: (MedCalc, RRID:SCR_015044)

    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:
    Major limitations of the study should be considered. First, properly designed controlled trials are urgently required to confirm the benefits of Ayurveda treatment. Second, without any pre-existing symptoms or medical conditions, in the healthy asymptomatic Covid-19 confirmed case, the role of Ayurveda intervention needs to be evaluated with caution. Finally, background therapies, including support interventions previously taken by participants, were not protocolled. Since the early outbreak, prophylactic support therapies (herbal supplements, Ayurveda, Homeopathy) have been recommended by the Government of India and are widely used by people. In conclusion, in asymptomatic Covid-19 confirmed cases, Ayurveda intervention can be considered a safe option. The results highlight the importance of curbing infection, which could limit the transmission of the virus to other people to curb the spread of Covid-19.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04542876CompletedEfficacy and Safety of Guduchi Ghan Vati in the Management o…


    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.