Randomized controlled trials of remdesivir in hospitalized coronavirus disease 2019 patients

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Abstract

The first cases of the coronavirus disease 2019 (COVID-19) were reported in Wuhan, China. No antiviral treatment options are currently available with proven clinical efficacy. However, preliminary findings from phase III trials suggest that remdesivir is an effective and safe treatment option for COVID-19 patients with both moderate and severe disease.

OBJECTIVE:

The aim of the present meta-analysis was to investigate whether remdesivir was effective for treating COVID-19 including reduced in-hospital adverse events, oxygen support, and mortality rates.

METHODS:

According to the PRISMA reporting guidelines, a review was conducted from January 1, 2020, until August 25, 2020, with MeSH terms including COVID-19, COVID, coronavirus, SARS-CoV-2, remdesivir, adenosine nucleoside triphosphate analog, and Veklury using MEDLINE, Scopus, and CINAHL Plus. A modified Delphi process was utilized to include the studies and ensure that the objectives were addressed. Using dichotomous data for select values, the unadjusted odds ratios (ORs) were calculated applying Mantel–Haenszel random-effects method in Review Manager 5.4.

RESULTS:

Randomized controlled trials pooled in 3013 participants with 46.3% ( n = 1395) in the remdesivir group and 53.7% ( n = 1618) in the placebo group. The placebo group had a higher risk of mortality as compared to the intervention group with significant OR (0.61) (95% confidence interval of 0.45–0.82; P = 0.001). There was minimal heterogeneity among the studies ( I 2 = 0%).

CONCLUSIONS:

Our findings suggest that remdesivir extends clinical benefits by reducing mortality, adverse events, and oxygen support in moderate to severely ill COVID-19 patients. Concerted efforts and further randomized placebo-controlled trials are warranted to examine the potency of antiviral drugs and immunopathological host responses contributing to the severity of COVID-19.

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  1. SciScore for 10.1101/2020.08.21.20179200: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationWe included studies if they were randomized control trials, had an intervention arm as compared to placebo, and the endpoint of interest was clinical outcomes and mortality.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: According to PRISMA reporting guidelines, a review was conducted from January 1 2020 until 6 August 2020 with MeSH terms including “COVID-19”, “coronavirus”, “SARS-CoV-2”, “COVID”, “remdesivir”, “adenosine nucleoside triphosphate analog”, “Veklury” using Medline, Scopus, and CINAHL Plus.
    MeSH
    suggested: (MeSH, RRID:SCR_004750)
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)

    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.