Evidence map›Paper›PMID 37293307›Full record

ArticleFrontiers in medicine2023

Improved clinical outcomes in response to a 12-week blended digital and community-based long-COVID-19 rehabilitation programme.

Jemma L Smith, Kevin Deighton, Aidan Q Innes, Marc Holl, Laura Mould, Zhining Liao, Patrick Doherty, Greg Whyte, James A King, Davina Deniszczyc and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Health economic outcomes and national economic impacts associated with Long COVID in England and Scotland.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    Article
  6. Article
  7. Assessment and management of post-COVID-19 pulmonary complications: a rapid review.European respiratory review : an official journal of the European Respiratory Society · 2026
    Review
  8. Article
  9. Review
  10. Article
  11. A Mixed-Methods Study Exploring the Feasibility of a Digital Combined Lifestyle Intervention for Patients With Post Covid-19 Condition.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Reporting of pre-existing multiple long-term conditions in physical rehabilitation for long COVID: a scoping review.European respiratory review : an official journal of the European Respiratory Society · 2024
    Article
  16. Review
  17. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 1 country.

Jemma L Smith *Nuffield Health, Epsom, United Kingdom.
Kevin Deighton *Nuffield Health, Epsom, United Kingdom.
Aidan Q InnesNuffield Health, Epsom, United Kingdom.
Marc HollNuffield Health, Epsom, United Kingdom.
Laura MouldNuffield Health, Epsom, United Kingdom.
Zhining LiaoNuffield Health, Epsom, United Kingdom.
Patrick DohertyDepartment of Health Sciences, University of York, York, United Kingdom.
Greg WhyteSchool of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom.
James A KingNational Centre for Sport and Exercise Medicine, Loughborough University, Loughborough, United Kingdom.
Davina DeniszczycNuffield Health, Epsom, United Kingdom.
Benjamin M KellyNuffield Health, Epsom, United Kingdom.
Nuffield Health · GBLiverpool John Moores University · GBManchester Metropolitan University · GBUniversity Hospitals of Leicester NHS Trust · GBUniversity of York · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Two million people in the UK are experiencing long COVID (LC), which necessitates effective and scalable interventions to manage this condition. This study provides the first results from a scalable rehabilitation programme for participants presenting with LC. Methods: 601 adult participants with symptoms of LC completed the Nuffield Health COVID-19 Rehabilitation Programme between February 2021 and March 2022 and provided written informed consent for the inclusion of outcomes data in external publications. The 12-week programme included three exercise sessions per week consisting of aerobic and strength-based exercises, and stability and mobility activities. The first 6 weeks of the programme were conducted remotely, whereas the second 6 weeks incorporated face-to-face rehabilitation sessions in a community setting. A weekly telephone call with a rehabilitation specialist was also provided to support queries and advise on exercise selection, symptom management and emotional wellbeing. Results: The 12-week rehabilitation programme significantly improved Dyspnea-12 (D-12), Duke Activity Status Index (DASI), World Health Orginaisation-5 (WHO-5) and EQ-5D-5L utility scores (all Discussion: The blended and community design of this rehabilitation model makes it scalable and meets the urgent need for an effective intervention to support patients experiencing LC. This rehabilitation model is well placed to support the NHS (and other healthcare systems worldwide) in its aim of controlling the impacts of COVID-19 and delivering on its long-term plan. Clinical trial registration: https://www.isrctn.com/ISRCTN14707226, identifier 14707226.

Indexed as

coronavirusdigital healthemotional wellbeingexercisefatigueSARS-CoV-2SeaCole

Identifiers

PMID37293307
PMCPMC10244528
OpenAlexW4377942661

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.