COVID-19: Can early home treatment with Azithromycin alone or with Zinc help prevent hospitalisation, death, and long-COVID-19? A review

  1. Philippe Lepere
  2. Bruno Escarguel
  3. Selda Yolartiran
  4. Claude Escarguel

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Abstract

Introduction

The effects of the SARS-CoV-2 pandemic continues to disrupt health systems worldwide, leading to population lockdowns in many countries. Preventing hospitalisation, death and long-COVID-19 with repurposed drugs remains a priority. Hydroxychloroquine (HCQ) and azithromycin (AZM) are the most commonly used in ambulatory care, with divergent results. With the aim of decentralizing early treatment to family practitioners, we addressed the question: Can early home treatment with AZM alone or with zinc help prevent hospitalisation, death, and long-COVID-19?

Methodology

We conducted a scoping review of articles published from 31 st December 2019 to 5 th November 2020 in Pubmed, Google Scholar, MedRxiv, and BioRxiv databases, and a review of undergoing clinical trials published in the Clinicaltrial.gov database.

Results

Many studies report on outpatient treatment with a combination of AZM + HCQ versus AZM alone, and few studies propose the addition of Zinc (Zn) to AZM. In addition, we identified 5 clinical trials currently recruiting individuals for early outpatient treatment with AZM. However, we failed in identifying any study or clinical trial conducted with family practitioners responding to our question.

Discussion

The antiviral, anti-inflammatory, immunomodulatory benefits of AZM + Zn make this drugs combination a good candidate therapy to treat flu-like-COVID-19 and atypical pneumoniae. The antibacterial action of AZM can also help disrupting the bacteria/virus cooperation that is poorly documented. Considering pros and cons of macrolide use (including antimicrobial resistance), we call for early use of this therapy by family practitioners for home treatment of individuals presenting mild or moderate symptoms under rigorous scientific guidance to prevent hospitalisation, death and long-COVID.

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  1. Version published to 10.1101/2020.12.29.20248975v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.12.29.20248975: (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

    No key resources detected.

    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.

  3. Version published to 10.1101/2020.12.29.20248975v1 on medRxiv