In-depth analysis of laboratory parameters reveals the interplay between sex, age, and systemic inflammation in individuals with COVID-19

This article has been Reviewed by the following groups

Read the full article

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2020.08.07.20170043: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Plots were created with ggplot2 R package (https://ggplot2.tidyverse.org) and edited in CorelDraw software.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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:
    The major limitation in our study is the lack of information regarding patient comorbidities and clinical outcome, other than admission to ICU. Patients admitted to ICU or that died from COVID-19, as well as those with comorbidities increasing the risk of severe disease [24], may display substantial variation in laboratory markers [25]. Overall, several abnormalities observed were accentuated in patients admitted to ICU, although we identified 10 markers that appeared to be more perturbed than others when compared to patients with COVID-19 not admitted to ICU. Interestingly, this included an elevated neutrophil count, which was not significantly different between COVID-19 and control patients overall. This may be related to increased bacterial co-infection in COVID-19 ICU patients, but also highlights potential differences between biomarkers associated with SARS-CoV-2 infection and those related to more severe disease. We also acknowledge that the differences seen in the temporal profiles may fall on a spectrum. Even though some laboratory values in COVID-19 patients fall in the normal range, they significantly differ from those patients without COVID-19. We also did not have information regarding the cause of any illness in the control group, the individuals without SARS-CoV-2 infection. It is important to remember that the differences we describe in COVID-19 may be relative to individuals with other infections and not necessarily healthy controls. This is, however, also a k...

    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.