Azithromycin in patients with COVID-19: a systematic review and meta-analysis

  1. Luis Ayerbe
  2. Carlos Risco-Risco
  3. Ivo Forgnone
  4. Maria Pérez-Piñar
  5. Salma Ayis

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Abstract

Background

Azithromycin has been widely used in the management of COVID-19. However, the evidence on its actual effects remains disperse and difficult to apply in clinical settings. This systematic review and meta-analysis summarizes the available evidence to date on the beneficial and adverse effects of azithromycin in patients with COVID-19.

Methods

The PRISMA 2020 statement criteria were followed. Randomized controlled trials (RCTs) and observational studies comparing clinical outcomes of patients treated with and without azithromycin, indexed until 5 July 2021, were searched in PubMed, Embase, The Web of Science, Scopus, The Cochrane Central Register of Controlled Trials and MedRXivs. We used random-effects models to estimate pooled effect size from aggregate data.

Results

The initial search produced 4950 results. Finally, 16 studies, 5 RCTs and 11 with an observational design, with a total of 22 984 patients, were included. The meta-analysis showed no difference in mortality for those treated with or without azithromycin, in observational studies [OR: 0.90 (0.66–1.24)], RCTs [OR: 0.97 (0.87–1.08)] and also when both types of studies were pooled together [with an overall OR: 0.95 (0.79–1.13)]. Different individual studies also reported no significant difference for those treated with or without azithromycin in need for hospital admission or time to admission from ambulatory settings, clinical severity, need for intensive care, or adverse effects.

Conclusions

The results presented in this systematic review do not support the use of azithromycin in the management of COVID-19. Future research on treatment for patients with COVID-19 may need to focus on other drugs.

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  1. Version published to 10.1093/jac/dkab404
  2. ScreenIT

    SciScore for 10.1101/2021.08.03.21261414: (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.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All the publications indexed up to the 5th of July 2021, in the following six databases were reviewed: PubMed, Embase, The Web of Science, Scopus, The Cochrane Central Register of Controlled
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    Statistical analysis was performed using the software STATA V.16.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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:
    This review has some limitations. Only one person extracted most of the data (LA). Even so, all data were checked for accuracy on repeated occasions and all analyses were conducted several times and checked by a senior statistician (SA). It is also possible that some publications may have been missed. The use of standard care, provided in addition to AZM in the intervention arm, and on its own in the comparison arm, was not described in detail in some studies. It is not clear how different this standard care was across the studies and how this may have affected the results. Some RCTs adjusted the treatment effect for confounders but not all did so. In those adjusted however, there was no considerable difference between the unadjusted and adjusted estimates, likely due to the balanced characteristics of the compared groups, achieved by randomization. The comprehensive search in six databases, and critical assessment of 16 studies, that added together a large number of patients, represent strengths of this review. The inclusion of both observational and interventional studies, based in different settings and looking at various outcomes, are also positive aspects of this research. Furthermore, the sensitivity analyses that was conducted adds consistency to the results. The use of a random effect model was a conservative choice. The overall estimate remained significant despite the increased width of the confidence intervals, providing support to the significance of the findings....

    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.

  3. Version published to 10.1101/2021.08.03.21261414v1 on medRxiv