Outcome of COVID-19 and Match-Population Analysis with Compassionate Use of Remdesivir

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Abstract

Abstract: Objectives:  To analyze treatment outcomes for patients with COVID-19 with and without compassionate use of Remdesivir. Methods:  A retrospective review of electronic medical records for patients who did not receive Remdesivir due to unavailability. Match-population analysis based on inclusion criteria for compassionate use Remdesivir of the patient population who received Remdesivir as reported in literature and patients without Remdesivir.  Results: Sixty-six percent of patients met the criteria for compassionate use Remdesivir, 41% required intensive care unit admission, 20% invasive ventilation, and 10% died. The median time of hospitalization for survivors was eight days.  In the separate group of patients who did not meet the criteria for compassion use Remdesivir, mortality among patients with CrCl > 30 ml min, an exclusion criterion, was significantly higher as compared with patients with CrCl < 30 ml min. Conclusion: When compared with previously reported data from patients who received compassionate use Remdesivir, our population had notably fewer patients requiring invasive ventilation. 

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  1. SciScore for 10.1101/2020.07.22.20160002: (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.

  2. SciScore for 10.1101/2020.07.22.20160002: (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 variableRemdesivir not available Baseline characteristics and Received compassionate Outcomes care Remdesivir (Grein J. et (RRH) al.) Out population had fewer males (63.2% vs. 75%) and notably fewer patients requiring mechanical ventilation (20.4% vs. 64%).

    Table 2: Resources

    Data from additional tools added to each annotation on a weekly basis.

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.