Treatment of Coronavirus Disease 2019 (COVID-19) Patients with Convalescent Plasma

  1. Eric Salazar
  2. Katherine K. Perez
  3. Madiha Ashraf
  4. Jian Chen
  5. Brian Castillo
  6. Paul A. Christensen
  7. Taryn Eubank
  8. David W. Bernard
  9. Todd N. Eagar
  10. S. Wesley Long
  11. Sishir Subedi
  12. Randall J. Olsen
  13. Christopher Leveque
  14. Mary R. Schwartz
  15. Monisha Dey
  16. Cheryl Chavez-East
  17. John Rogers
  18. Ahmed Shehabeldin
  19. David Joseph
  20. Guy Williams
  21. Karen Thomas
  22. Faisal Masud
  23. Christina Talley
  24. Katharine G. Dlouhy
  25. Bevin V. Lopez
  26. Curt Hampton
  27. Jason Lavinder
  28. Jimmy D. Gollihar
  29. Andre C. Maranhao
  30. Gregory C. Ippolito
  31. Matthew O. Saavedra
  32. Concepcion C. Cantu
  33. Prasanti Yerramilli
  34. Layne Pruitt
  35. James M. Musser

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Abstract

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  1. Version published to 10.1016/j.ajpath.2020.05.014
  2. ScreenIT

    SciScore for 10.1101/2020.05.08.20095471: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was conducted at the Houston Methodist hospitals from March 28, 2020, through April 28, 2020, with the approval of the Houston Methodist Research Institute ethics review board and with informed patient or legally-authorized representative consent.
    Consent: All donors provided written informed consent and tested negative for SARS-CoV-2 by RT-PCR.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Donors were negative for anti-HLA antibodies, hepatitis B, C, HIV, HTLV I/II, Chagas disease, WNV, Zika virus, and syphilis per standard blood banking practices.
    anti-HLA
    suggested: None
    Software and Algorithms
    SentencesResources
    Whole genome alignments of consensus viral genome sequence generated from the ARTIC nCoV-2019 bioinformatics pipeline were trimmed to the start of orf1ab and the end of orf10 and used to generate a phylogenetic tree using RAxML (https://cme.h-its.org/exelixis/web/software/raxml/index.html) to determine viral clade.
    RAxML
    suggested: (RAxML, RRID:SCR_006086)

    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:
    Limitations: As with the great majority of the studies using convalescent plasma to treat severe infections, our study has several important limitations. First, the study was a small case series and no control group was included. Thus, it is not clear if the 25 patients given convalescent plasma would have improved without this treatment. Second, all patients were treated with multiple other medications, including antiviral and anti-inflammatory agents. Thus, we cannot conclude that the patient outcomes were solely due to administration of convalescent plasma. Third, 24 of the 25 patients received only one transfusion of plasma. Whether treatment with multiple transfusions on one or more days would be a more effective regimen is not clear. An expanded donor pool providing higher-titer convalescent plasma would allow for dose escalation studies. Fourth, many patients had severe COVID-19 disease. It is possible that transfusion of convalescent plasma earlier in the course of disease or in patients with less severe symptoms would be a better approach. Fifth, our plasma donors had a range of anti-S protein IgG titers. Several patients were transfused with plasma with very low titer of anti-S protein antibody. Sixth, the small number of patients treated, coupled with the experimental design, did not permit us to determine if this therapy significantly reduces mortality or other measures of disease outcome. Finally, while this study assessed outcomes at days 7 and 14 post-transfusi...

    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 10.1101/2020.05.08.20095471v1 on medRxiv