Serological Cytokine and chemokine profile in pregnant women with COVID19 in Mexico City

  1. Arturo Cerbulo-Vazquez
  2. Berenice Zavala-Barrios
  3. Jesus Carlos Briones-Garduno
  4. Guadalupe Mercedes Lucia Guerrero-Avendano
  5. Lourdes Arriaga-Pizano
  6. Eduardo Ferat-Osorio
  7. Graciela Libier Cabrera-Rivera
  8. Patricia Miranda-Cruz
  9. Maria Teresa Garcia de la Rosa
  10. Jessica Lakshmi Prieto-Chavez
  11. Vanessa Rivero-Arredondo
  12. Ruth Madera-Sandoval
  13. Alonso Cruz-Cruz
  14. Enrique Salazar-Rios
  15. David Serrano-Molina
  16. Roberto De Lira-Barraza
  17. Abel Humberto Villanueva-Compean
  18. Alejandra Esquivel-Pineda
  19. Ruben Ramirez-Montes de Oca
  20. Guillermo Flores-Padilla
  21. Constantino Lopez-Macias

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Abstract

On January 30th, 2020, the WHO declared the outbreak of COVID19, a disease due to the new coronavirus called SARS-CoV-2. Certain comorbidities, symptoms and signs are characteristic of COVID19 in the general population and in pregnant women. However, pregnant women are considered as a high-risk group for COVID19. To know about the frequency of comorbidities, signs and symptoms, the presence of lymphopenia, antibodies response to SARS-CoV2 and cytokine and chemokine serum concentration, six pregnant women with COVID19 were studied at the moment of admission. The lower concentration of CCL17 was detected in the Pregnant COVID19 group, similar concentration of IL-6 was also detected in non-pregnant and pregnant COVID19 patients. Our result show that pregnant and non-pregnant women with COVID19 has similar cytokine profile.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.14.20153585: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Eighteen women were enrolled after obtaining a signed informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableEighteen women were enrolled after obtaining a signed informed consent.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical Analysis: Statistical analysis was performed using Graph Pad Prism® version 6 software (GraphPad Software, San Diego, CA, USA), and SPSS software, compilation 1.0.0.1347.
    Graph Pad Prism®
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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:
    However, the limitation is the small number of cases for analysis, due to the time when the pregnant patients requested medical attention, and it was not possible to monitor them for a long time. There are few studies available about the effect of COVID19 in pregnancy and it has published that pregnant women with COVID are not sufficiently taken into account in clinical research (51), especially in immunology. This is important because contrary to assume that pregnancy in COVID19 could lead to high number of fatal outcomes such as SARS (27), despite data shows just the opposite. So, if pregnancy is a condition were the immune system is capable to handle this viral challenge we must to learn more about tolerance in immune response in pregnancy, and apply that knowledge to successful treatment for the non-pregnant patients.

    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 10.1101/2020.07.14.20153585 on medRxiv