ROLE OF ANTIBODIES, INFLAMMATORY MARKERS, AND ECHOCARDIOGRAPHIC FINDINGS IN POST-ACUTE CARDIOPULMONARY SYMPTOMS AFTER SARS-COV-2 INFECTION

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2021.11.24.21266834: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Study Approval: All participants provided signed written informed consent prior to participation.
    IRB: Institutional Review Board approval was granted by the University of California, San Francisco. Dr.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    BlindingA blinded cardiac sonographer performed echocardiograms using a standardized protocol with a GE VIVID E90 machine.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Echocardiograms were measured and post-processed by a single echocardiographer with GE EchoPAC software.
    GE EchoPAC
    suggested: None
    Data were recorded using REDCap.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    Statistical analyses were performed using StataMP 16.1 (StataCorp, College Station, TX).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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:
    Study Limitations: Limitations of this study include the use of a convenience sample and the cross-sectional echocardiographic and biomarker assessments. There is a risk of selection bias from those in the LIINC study who chose to participate in the cardiovascular sub-study, and from the shift in our recruitment criteria toward those with symptoms. To date, there are no formal definitions of cardiopulmonary PASC. We did not have echocardiograms from prior to or during acute infection to examine sub-clinical changes among our sample. Because we are specifically interested in the pathophysiology of persistent symptoms compared to those who fully recover from COVID-19, we intentionally did not include a SARS-CoV-2 uninfected control group, but inclusion of such a control group would have strengthened our inferences. We excluded those with pre-existing heart failure, congenital heart disease, and pulmonary hypertension, so our findings may not be generalizable to those with pre-existing cardiac disease. Third, because we only included a small number of people who received intensive care during acute COVID-19 and none with myocarditis in the setting of acute disease, our findings may not be applicable to those with the highest severity of illness. Finally, the number with pericardial effusions is small so findings particularly with respect to biomarkers and pericardial effusions should be confirmed in larger studies.

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

    IdentifierStatusTitle
    NCT04362150RecruitingLong-term Impact of Infection With Novel Coronavirus (COVID-…


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 33. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.


    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.