Postcoronavirus disease-2019 symptoms are not uncommon among recovered patients: A cross-sectional online survey among the Indian population

  1. Vishwanath Gella
  2. D. Nageshwar Reddy
  3. Anand V. Kulkarni
  4. Jagdeesh Kumar
  5. Madhuri Radhakrishnan
  6. Robin Chatterjee
  7. Venkat Rao Guduru

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Abstract

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  1. Version published to 10.4103/lungindia.lungindia_541_21
  2. ScreenIT

    SciScore for 10.1101/2021.07.15.21260234: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The institutional ethics committee approved the study vide letter no. AIG/IEC-Post BH&R 15/06/2021-07.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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 limitation of our survey is we did not capture the data on age and comorbidities of the patients who reported symptoms. However, to our knowledge, this is the first Indian study to report a high incidence of post-COVID-19 symptoms among COVID-19 recovered individuals. Both hospitalized and non-hospitalized patients suffer from post-COVID-19 symptoms. Furthermore, the injudicious use of steroids led to a significant increase in the risk of post-COVID-19 symptoms.

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2021.07.15.21260234 on medRxiv