ReCOVer study: A Cross-sectional Observational Study to Identify the Re habilitation Need in Post-discharge COV ID-19 Survivors

  1. Raktim Swarnakar
  2. S. L. Yadav
  3. V Srikumar
  4. Kapil Dev Soni
  5. Richa Aggrawal
  6. Anjan Trikha

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Abstract

Introduction

With the increasing number of Coronavirus disease-2019 (COVID-19) cases there is simultaneous increase in recovered cases too. There are many post-covid complications where need for rehabilitation intervention is very conspicuous especially pulmonary, neurological complications. Hence data are of utmost importance to find out those rehabilitation needs among post-covid survivors.

Methods and analysis

ReCOVer ( Re habilitation Need in Post-discharge COV ID-19 Survivors), a cross-sectional observational study protocol has been planned to find out rehab-need by assessing International Classification of Functioning, Disability and Health (ICF) core data set, COVID-19 Yorkshire Rehab Screen (C19-YRS) tool, The Post-COVID-19 Functional Status (PCFS) scale, barriers to functional independence and rehab services (affordability & availability). Post-discharge (minimum 1 weeks) Covid patients (required hospitalisation) will be included in the study. Study will be conducted through Telerehabilitation facility. Study will conform to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Ethics and dissemination

Study received ethical approval from Institute Ethics Committee, All India Institute of Medical Sciences (AIIMS), New Delhi, India. Findings will be disseminated at scientific conferences/meetings, peer-reviewed journals, and to relevant stakeholders including the ministry of health (if required).

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  1. ScreenIT

    SciScore for 10.1101/2021.04.19.21255750: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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 10.1101/2021.04.19.21255750v1 on medRxiv