Post COVID-19 sequelae: A prospective observational study from Northern India

  1. Shivdas Naik
  2. Soumendra Nath Haldar
  3. Manish Soneja
  4. Netto George Mundadan
  5. Prerna Garg
  6. Ankit Mittal
  7. Devashish Desai
  8. Praveen Kumar Trilangi
  9. Sayan Chakraborty
  10. Nazneen Nahar Begam
  11. Bisakh Bhattacharya
  12. Ganesh Maher
  13. Niranjan Mahishi
  14. Chaithra Rajanna
  15. Swasthi S Kumar
  16. Bharathi Arunan
  17. J Kirtana
  18. Ankesh Gupta
  19. Diksha Patidar
  20. Parul Kodan
  21. Prayas Sethi
  22. Animesh Ray
  23. Pankaj Jorwal
  24. Arvind Kumar
  25. Neeraj Nischal
  26. Sanjeev Sinha
  27. Ashutosh Biswas
  28. Naveet Wig

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.5582/ddt.2021.01093
  2. ScreenIT

    SciScore for 10.1101/2021.06.28.21259658: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Verbal consent was taken before the enrolment.
    IRB: The study protocol was approved by the institutional ethics committee.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The data was analysed using STATA 16.0 software.
    STATA
    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 had a few limitations. Loss to follow up is inherent in all cohort studies, and this was exacerbated in our study due to significant social upheaval and mobility restrictions during the pandemic. Due to mobility restrictions and limited services during the pandemic surge, data on laboratory workup and imaging of patients could not be collected systematically, which may have shed light on their pathogenesis, clinical course and management.

    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.

    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.

  3. Version published to 10.1101/2021.06.28.21259658v1 on medRxiv