학술논문
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)
Document Type
article
Author
Samantha Jones; Helen Davies; Stavros Petrou; Simon de Lusignan; Carlos Echevarria; Iram Qureshi; Trisha Greenhalgh; Jonathan Clarke; Johnny Collett; Helen Dawes; Ben Glampson; Joseph Kwon; Vasa Curcin; Brendan Delaney; Clare Rayner; Erik Mayer; Gayathri Delanerolle; Manoj Sivan; Daryl O’Connor; Darren C Greenwood; Mike Horton; Sarah Elkin; Mauricio Barahona; Nawar Diar Bakerly; Rachael Evans; Ruairidh Milne; Anton Pick; Ghazala Mir; Joanna Dawes; Amy Parkin; Stephen Halpin; Nick Preston; Alexander Casson; Tomas Ward; Harsha Master; Emma Tucker; Maedeh Mansoubi; Aishwarya Bhatia; Himanshu Vashisht; Leisle Ezekiel; Phaedra Leveridge; Flo Read; Ian Tuckerbell; Willie Muhlhausen; Zaccheus Falope; Jacqui Morris; Amy Rebane; Ana Belen Espinosa Gonzalez; Sareeta Baley; Annette Rolls; Emily Bullock; Megan Ball; Shehnaz Bashir; Joanne Elwin; Denys Prociuk
Source
BMJ Open, Vol 13, Iss 8 (2023)
Subject
Language
English
ISSN
2044-6055
Abstract
Introduction A 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.