Convalescent plasma associates with reduced mortality and improved clinical trajectory in patients hospitalized with COVID-19

  1. Shanna A. Arnold Egloff
  2. Angela Junglen
  3. Joseph S.A. Restivo
  4. Marjorie Wongskhaluang
  5. Casey Martin
  6. Pratik Doshi
  7. Daniel Schlauch
  8. Gregg Fromell
  9. Lindsay E. Sears
  10. Mick Correll
  11. Howard A. Burris
  12. Charles F. LeMaistre

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Abstract

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  1. Version published to 10.1172/jci151788
  2. ScreenIT

    SciScore for 10.1101/2021.06.02.21258190: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This research was performed under a master retrospective protocol (MR 01) approved under expedited review by an external governing institutional review board (IntegReview/Advarra) and granted a waiver of informed consent.
    Consent: This research was performed under a master retrospective protocol (MR 01) approved under expedited review by an external governing institutional review board (IntegReview/Advarra) and granted a waiver of informed consent.
    Sex as a biological variablenot detected.
    RandomizationThe comparison group was randomly assigned a pseudo-baseline prior to matching that reflected equal distribution of the time interval from admission to transfusion as the CP group (Supplemental Materials, Pseudo-Baseline).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    We were able to obtain Ortho Vitros serology signal to cut-off ratio (S/Co) data measuring total anti-SARS-CoV-2 antibodies from blood-bank suppliers for a subset of patients treated with CP.
    anti-SARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    Outcomes Measures: Statistics: Human Participants and Study Approval: This study was supported by HCA Healthcare and conducted in accordance with US regulations, applicable ICH E6 international standards of Good Clinical Practice, and institutional research policies and procedures.
    HCA Healthcare
    suggested: None
    Matching and Covariates: A variety of patient characteristics were captured at baseline that were considered for matching criteria.
    Covariates
    suggested: None

    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:
    Although we made substantial efforts to manage challenges of analyzing real-world data, there are limitations inherent in their use. These include the evolution of diagnosis and treatment during this pandemic as well as changes in medical documentation and coding related to COVID-19 across multiple facilities. We attempted to account for this by matching on calendar epochs, controlling for calendar date, and nesting on facility. Neither BMI nor smoking status could be included in our analyses due to unreliability and missingness, respectively. Incorporating days from symptom onset to transfusion, rather than days from admission, could more accurately identify optimal timing of CP transfusion. However, less than 10% of patients had clear reporting of symptom onset and, thus, we could not confidently execute analyses with symptom onset due to missingness. In addition, although concomitant medications were controlled for in all primary, secondary and subgroup analyses, they were treated as indicators during hospitalization rather than accounting for their timing with CP and dose. Future studies will be directed at evaluating medication interactions with CP and identifying optimal dosing and timing of concomitant medications. A challenge to retrospectively evaluating CP delivered in the community setting has been the evolution of treatment criteria and access to CP. The CP cohort was skewed to higher severity based on eligibility criteria for EAP enrollment criteria prior to appr...

    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 10.1101/2021.06.02.21258190v1 on medRxiv