In-hospital use of ACE inhibitors/angiotensin receptor blockers associates with COVID-19 outcomes in African American patients

  1. Shilong Li
  2. Rangaprasad Sarangarajan
  3. Tomi Jun
  4. Yu-Han Kao
  5. Zichen Wang
  6. Ke Hao
  7. Emilio Schadt
  8. Michael A. Kiebish
  9. Elder Granger
  10. Niven R. Narain
  11. Rong Chen
  12. Eric E. Schadt
  13. Li Li

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Abstract

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  1. Version published to 10.1172/jci151418
  2. ScreenIT

    SciScore for 10.1101/2021.04.14.21255443: (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 AnalysisWe also applied the Wald-based power and sample size formulas for logistic regression to calculate the power given the observed sample size.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We performed all analysis using R (version 4.0.1) and Python (version 3.7).
    Python
    suggested: (IPython, RRID:SCR_001658)

    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: Our study has several limitations. It was a retrospective study and cannot establish a causal relationship between ACE-I/ARB and COVID-19 outcomes via the ACE D-allele without individual-level germline genetic data and prospective treatment assignment. Secondly, our study is based on a single center experience and these analyses should be repeated in other cohorts. Finally, while outpatient medication adherence could not be verified, this EMR dataset draws on multiple data sources to bolster accuracy and comprehensiveness.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04366050RecruitingRamipril for the Treatment of COVID-19

    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 10.1101/2021.04.14.21255443 on medRxiv