Evidence map›Paper›PMID 37553189›Full record

ArticleBMJ open2023

Digital home monitoring for capturing daily fluctuation of symptoms; a longitudinal repeated measures study: Long Covid Multi-disciplinary Consortium to Optimise Treatments and Services across the NHS (a LOCOMOTION study).

Maedeh Mansoubi, Joanna Dawes, Aishwarya Bhatia, Himanshu Vashisht, Johnny Collett, Darren C Greenwood, Leisle Ezekiel, Daryl O'Connor, Phaedra Leveridge, Clare Rayner and 8 more

Abstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

18 authors.

Maedeh MansoubiNIHR Exeter Biomedical Research Center, Medical School, Faculty of Health and Life sciences, University of Exeter, Exeter, UK.ORCID 0000-0002-8829-2217
Joanna DawesMedical School, University of Exeter, Exeter, UK.
Aishwarya BhatiaMedical School, University of Exeter, Exeter, UK.
Himanshu VashishtIn The Wild Research Limited, Dublin, Ireland.
Johnny CollettDepartment of Sport, Health and Social Work, Oxford Brookes University, Oxford, UK.
Darren C GreenwoodAcademic Department of Rehabilitation Medicine, University of Leeds, Leeds, UK.ORCID 0000-0001-7035-3096
Leisle EzekielSchool of Health Sciences, University of Southampton, Southampton, UK.
Daryl O'ConnorSchool of Psychology, University of Leeds, Leeds, UK.ORCID 0000-0003-4117-4093
Phaedra LeveridgeDepartment of Public Health and Sport Sciences, University of Exeter, Exeter, UK.ORCID 0000-0002-3602-2231
Clare RaynerPatient Advisory Group (PAG) Representative, Leeds, UK.
Flo ReadDepartment of Health and Community Sciences, University of Exeter, Exeter, UK.
Manoj SivanFaculty of Medicine and Health, School of Medicine, University of Leeds, Leeds, UK.ORCID 0000-0002-0334-2968
Ian TuckerbellPatient Advisory Group (PAG) Representative, Leeds, UK.
Tomas WardInsight SFI Research Centre for Data Analytics, Dublin City University, Dublin, Ireland.
Brendan DelaneyFaculty of Medicine, Department of Surgery & Cancer, Imperial College, London, UK.
Willie MuhlhausenIn The Wild Research Limited, Dublin, Ireland.
Locomotion consortium
Helen DawesNIHR Exeter Biomedical Research Center, Medical School, Faculty of Health and Life sciences, University of Exeter, Exeter, UK h.dawes@exeter.ac.uk.ORCID 0000-0002-2933-5213

Funding

Department of Health
6 · The paper itself

Abstract

introductionA substantial proportion of COVID-19 survivors continue to have symptoms more than 3 months after infection, especially of those who required medical intervention. Lasting symptoms are wide-ranging, and presentation varies between individuals and fluctuates within an individual. Improved understanding of undulation in symptoms and triggers may improve efficacy of healthcare providers and enable individuals to better self-manage their Long Covid. We present a protocol where we aim to develop and examine the feasibility and usability of digital home monitoring for capturing daily fluctuation of symptoms in individuals with Long Covid and provide data to facilitate a personalised approach to the classification and management of Long Covid symptoms. METHODS AND ANALYSIS: This study is a longitudinal prospective cohort study of adults with Long Covid accessing 10 National Health Service (NHS) rehabilitation services in the UK. We aim to recruit 400 people from participating NHS sites. At referral to study, 6 weeks and 12 weeks, participants will complete demographic data (referral to study) and clinical outcome measures, including ecological momentary assessment (EMA) using personal mobile devices. EMA items are adapted from the COVID-19 Yorkshire Rehabilitation Scale items and include self-reported activities, symptoms and psychological factors. Passive activity data will be collected through wrist-worn sensors. We will use latent class growth models to identify trajectories of experience, potential phenotypes defined by co-occurrence of symptoms and inter-relationships between stressors, symptoms and participation in daily activities. We anticipate that n=300 participants provide 80% power to detect a 20% improvement in fatigue over 12 weeks in one class of patients relative to another. ETHICS AND DISSEMINATION: The study was approved by the Yorkshire & The Humber-Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Findings will be disseminated in peer-reviewed publications and presented at conferences. TRIAL REGISTRATION NUMBER: ISRCTN15022307.

Indexed as

COVID-19HumansPost-Acute COVID-19 SyndromeProspective StudiesResearch DesignState MedicineCOVID-19FatiguePAIN MANAGEMENTRehabilitation medicine

Identifiers

PMID37553189
PMCPMC10414119

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.