Pre-existing conditions are associated with COVID-19 patients’ hospitalization, despite confirmed clearance of SARS-CoV-2 virus

  1. Colin Pawlowski
  2. AJ Venkatakrishnan
  3. Eshwan Ramudu
  4. Christian Kirkup
  5. Arjun Puranik
  6. Nikhil Kayal
  7. Gabriela Berner
  8. Akash Anand
  9. Rakesh Barve
  10. John C. O'Horo
  11. Andrew D. Badley
  12. Venky Soundararajan

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Abstract

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  1. Version published to 10.1016/j.eclinm.2021.100793
  2. Version published to 10.1101/2020.10.28.20221655v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.10.28.20221655: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Institutional Review Board (IRB): This retrospective research was conducted under IRB 20–003278, ‘Study of COVID-19 patient characteristics with augmented curation of Electronic Health Records (EHR) to inform strategic and operational decisions’.
    Consent: For further information regarding the Mayo Clinic Institutional Review Board (IRB) policy, and its institutional commitment, membership requirements, review of research, informed consent, recruitment, vulnerable population protection, biologics, and confidentiality policy, please refer to www.mayo.edu/research/institutional-review-board/overview.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    This is a qualitative ELISA for detection of IgG-class antibodies against a recombinant version of the SARS-CoV-2 spike subunit 1 (S1) protein and has received Food and Drug Administration Emergency Use Authorization.
    SARS-CoV-2 spike subunit 1
    suggested: None
    Software and Algorithms
    SentencesResources
    This test was applied using the SciPy package18 in Python. p-values generated in this hypothesis were corrected using a Benjamini-Hochberg correction.
    SciPy
    suggested: (SciPy, RRID:SCR_008058)
    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:
    Additionally, a limitation of our study is that our algorithm did not include all forms of obstructive airway disease, including COPD, which has been indicated to increase mortality in COVID-1923. Despite these caveats, our finding that pre-COVID anemia is endemic or highly prevalent in several low- and middle-income countries23, where COVID-19 is unfortunately a raging pandemic (e.g. India and Brazil) is especially concerning from the standpoint of higher post-viral clearance hospitalization risk in COVID patients. A point of interest in explaining heterogeneous outcomes as regards hospital admission following SARS-CoV-2 viral clearance is the development of IgG antibodies post-clearance. In the context of this study 16 of 23 patients (69.5%) in the hospitalized post-clearance cohort tested for IgG antibodies test positive; this is compared to a rate of 19 of 23 patients (82.6%) in the non-hospitalized post-clearance cohort. The difference between these groups (16/23 vs. 19/23; fisher exact p-value 0.49) is not significant in this case. However, as the antibody testing data increases further investigation into the relationship between IgG seropositivity and complications following SARS-CoV-2 clearance may be warranted. There are several limitations of this study due to the observational nature of the data. First, we are not controlling for PCR testing frequency, so the study population which receives access to multiple PCR tests to confirm SARS-CoV-2 infection clearance may ...

    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.

  4. Version published to 10.1101/2020.10.28.20221655v1 on medRxiv