Influence of sex on disease severity in children with COVID-19 and Multisystem Inflammatory Syndrome in Latin America

  1. Martin Brizuela
  2. Jacopo Lenzi
  3. Rolando Ulloa-Gutiérrez
  4. Antúnez-Montes Omar Yassef
  5. Jorge Alberto Rios Aida
  6. Olguita del Aguila
  7. Erick Arteaga-Menchaca
  8. Francisco Campos
  9. Fadia Uribe
  10. Andrea Parra Buitrago
  11. Lina Maria Betancur Londoño
  12. Jessica Gómez-Vargas
  13. Adriana Yock-Corrales
  14. Danilo Buonsenso

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Abstract

Data from adult studies how that COVID-19 is more severe in men than women. However, no data are available for the pediatric population. For this reason, we performed this study aiming to understand if sex influenced disease severity and outcomes in a large cohort of latin-american children with COVID-19 and Multisystem Inflammatory Syndrome (MIS-C). We found that a higher percentage of male children developed MIS-C (8.9% vs 5% in females) and died (1.2% and 0.4% in females), although on multivariate adjusted analyses the only statistically significant difference was found in need of hospitalization, with females less frequently admitted compared with boys (25.6% vs 35.4%). This data are preliminary and need further independent studies to better assess the role of sex.

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  1. ScreenIT

    SciScore for 10.1101/2021.02.07.21251212: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was reviewed and approved by the CoviD in sOuth aMerIcaN children—study GrOup core group and approved by the Ethics Committee of the coordinating center and by each participating center (Mexico: COMINVETICA-30072020-CEI0100120160207; Colombia: PE-CEI-FT-06; Peru: No. 42-IETSI-ESSALUD-2020; Costa Rica: CEC-HNN-243-2020).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableThe association between female sex and COVID-19 clinical outcomes was preliminarily evaluated with crude odds ratios (ORs) and 95% confidence intervals (CIs).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    College Station, TX: StataCorp LLC).
    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:
    Our study has limitation to address. First, it was not initially developed to specifically address how sex could influence disease severity, therefore the variables included as well the study power was not tailored to this topic. Also, blood tests, hormones and Vitamin D were not tested and therefore not analyzed. Last, there is no a control group of adult patients from the same area to compare sex differences in different age groups. However, this study is the first one specifically assessing the role of sex in children with COVID-19 and MIS-C. In conclusion, we found that a slightly more severe course of COVID-19 and MIS-C in boys compared with women in our cohort of Latin American children. This data are preliminary and need further independent studies to better assess the role of sex. In light of the growing evidence of long covid in children, it is important to begin including sex as an important potential variable of severity or symptoms persistence in children with COVID-19.

    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.

  2. Version published to 10.1101/2021.02.07.21251212v1 on medRxiv