Protocol for mixed-method study by LOng COvid Multidisciplinary consortium: Optimising Treatments and servIces acrOss the NHS (LOCOMOTION)

  1. Manoj Sivan
  2. Trisha Greenhalgh
  3. Julie L. Darbyshire
  4. Ghazala Mir
  5. Rory J. O’Connor
  6. Helen Dawes
  7. Darren C. Greenwood
  8. Daryl B. O’Connor
  9. Mike Horton
  10. Stavros Petrou
  11. Simon de Lusignan
  12. Vasa Curcin
  13. Erik Mayer
  14. Alexander Casson
  15. Ruairidh Milne
  16. Clare Rayner
  17. Nikki Smith
  18. Amy Parkin
  19. Nick Preston
  20. Brendan Delaney

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Abstract

Introduction

Long COVID, a new condition whose origins and natural history are not yet fully established, currently affects 1.5 million people in the UK. Most do not have access to specialist long COVID services. We seek to optimise long COVID care both within and outside specialist clinics, including improving access, reducing inequalities, helping patients manage their symptoms effectively at home, and providing guidance and decision support for primary care. We aim to establish a ‘gold standard’ of care by systematically analysing symptom clusters and current practices, iteratively improving pathways and systems of care, and working to disseminate better practices.

Methods and analysis

This mixed-method, multi-site study is informed by the principles of applied health services research, quality improvement, co-design, and learning health systems. It was developed in close partnership with patients (whose stated priorities are prompt clinical assessment; evidence-based advice and treatment; and help with returning to work and other roles) and with front-line clinicians. Workstreams and tasks to optimise assessment, treatment and monitoring are based in three contrasting settings: [1] specialist management in 10 long COVID clinics across the UK, via a quality improvement collaborative, experience-based co-design and targeted efforts to reduce inequalities of access; [2] patient self-management at home, with technology-supported monitoring; and [3] generalist management in primary care, harnessing electronic record data to study population phenotypes and develop evidence-based decision support, referral pathways and prioritisation criteria across the primary-secondary care interface, along with analysis of costs. Study governance includes an active patient advisory group.

Ethics and dissemination

LOCOMOTION is sponsored by the University of Leeds and approved by Yorkshire & The Humber - Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers to influence service specifications and targeted funding streams.

Study registration

ClinicalTrials.gov : NCT05057260 ; ISRCTN15022307 .

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  1. ScreenIT

    SciScore for 10.1101/2022.04.09.22273655: (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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT05057260Not yet recruitingLOng COvid Multidisciplinary Consortium: Optimising Treatmen…
    ISRCTN15022307NANA

    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.

  2. Version published to 10.1101/2022.04.09.22273655v1 on medRxiv