Understanding Patterns of Fatigue in Health and Disease
NCT ID: NCT05622669
Last Updated: 2024-04-05
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ACTIVE_NOT_RECRUITING
40 participants
OBSERVATIONAL
2021-12-07
2024-03-30
Brief Summary
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Participants will wear ECG patches and wrist-worn sensors that measure heart rate variability, activity levels, posture, and other parameters. They will self-rate their levels of fatigue four times daily and on-demand (when fatigue levels are noticeably good or troublesome). They will participate in an end of study interview and will have an optional feedback session with a researcher to make sense of the data they have provided.
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Detailed Description
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This feasibility study will investigate patient experiences of fatigue in depth, combining objective measures of sensed physiological parameters with patient reports and validated patient reported outcome measures. Patients will be recruited with three distinct clinical conditions: myeloma; long COVID; and heart failure. A healthy control group will also be recruited.
Participants will participate in a feasibility study with a longitudinal, Ecological Momentary Assessment (EMA) design, wearing sensors, and providing four times daily short self-reports of fatigue over a two-to-four week period (to be determined by the individual participant and their preferences and patterns of fatigue). They will complete validated fatigue, affect, and interoceptive awareness scores at baseline and at two weeks and participate in end of study telephone interviews with a Research Assistant.
Sensors will measure objective parameters including activity levels; heart rate; sleep; and posture (sitting/standing). Additional sensors ("beacons") will measure participant's movements and positioning within their own environment (position relative to the beacons - beacon location to be determined by participant placement); environmental temperature; noise and light levels.
Data will be analysed using multilevel modelling and Machine Learning to detect patterns in the fatigue experiences and to compare fatigue measurements within individuals; between individuals with the same clinical condition; and between groups of individuals with different clinical conditions/controls.
This feasibility study will provide data that helps to determine:
* The utility and usefulness of different sensed parameters in understanding the fatigue experience
* The practicality and acceptability of collecting the proposed sensed and self-reported data and recruitment and retention rates (to inform a larger study)
* Whether there might be meaningful differences in fatigue between individuals and groups of individuals with distinct medical conditions
* Whether there is scope for a larger study into clinical "phenotypes" of fatigue (distinct classes of fatigue that might vary according to different combinations of physiological signatures, different patient descriptions/language used to describe the experience, diurnal variation, etc.)
Conditions
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Study Design
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ECOLOGIC_OR_COMMUNITY
PROSPECTIVE
Study Groups
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Myeloma
Individuals experiencing fatigue related to myeloma or its treatment
Observational
Sensed and lived experience data from all groups without a specific behavioural or drug intervention
Long COVID
Individuals experiencing fatigue related to Long COVID
Observational
Sensed and lived experience data from all groups without a specific behavioural or drug intervention
Heart failure
Individuals experiencing fatigue related to heart failure or its treatment
Observational
Sensed and lived experience data from all groups without a specific behavioural or drug intervention
Controls
Individuals who are not experiencing problematic fatigue and who do not have myeloma, long COVID, or heart failure
Observational
Sensed and lived experience data from all groups without a specific behavioural or drug intervention
Interventions
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Observational
Sensed and lived experience data from all groups without a specific behavioural or drug intervention
Eligibility Criteria
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Inclusion Criteria
* A confirmed diagnosis of myeloma
* Has experienced fatigue that is perceived by the participant to be worse than "normal tiredness" and that they associate with myeloma or treatment for myeloma
* A formal diagnosis of heart failure
* All stages of heart failure and all aetiologies and with no specific ejection fraction cut-off
* Has experienced fatigue that is perceived by the participant to be worse than "normal tiredness" and that they associate with their cardiac disease or its treatment
* Experiencing fatigue that is perceived by the participant to be worse than "normal tiredness", with or without other physical or psychological symptoms that developed during or after an infection consistent with COVID-19
* The fatigue (plus or minus any other symptoms) has continued for greater or equal to 12 weeks, and is not explained by an alternative diagnosis
• Individuals aged 18 years or over without the disease conditions specified in Groups A to C
Exclusion Criteria
* Adults lacking capacity to consent
* Under 18 years of age
* Declines to participate
* Under investigation for or starting treatment for an endocrine, metabolic, or thyroid condition where the participant has not been established on a stable therapeutic dose of a licensed therapy for that condition
* A confirmed diagnosis of sleep apnoea or narcolepsy
* HADs depression and anxiety score at baseline greater than 8 on the depression questions, which might indicate untreated or undertreated depression
* Shift work that involves overnight working between the hours of 9pm and 9am
We will not exclude patient participants in groups A to C based on the type of prescribed medications that they are taking. Instead, this will be carefully documented.
For Group A, myeloma
* Uncontrolled hypercalcaemia
* Current or previous diagnosis of heart failure or long COVID
* An active primary cancer diagnosis other than myeloma Group B Heart Failure
* A current or previous diagnosis of myeloma or long COVID
* Active cancer Group C, long COVID
* A current or previous diagnosis of myeloma or heart failure
* Active cancer Group D, Control group
* Presence of myeloma or another active cancer, heart failure, or long COVID
* One or more chronic medical conditions which are unstable, poorly controlled, AND perceived by the individual to be causing fatigue
* Persistent or severe fatigue symptoms that are perceived by the individual to be worse than "normal tiredness"
* Taking sedating medications to manage anxiety or insomnia including but not limited to benzodiazepines or "Z" drugs, zopiclone, zolpidem, and others in this British National Formulary Class.
18 Years
ALL
Yes
Sponsors
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University of Cambridge
OTHER
University of Glasgow
OTHER
Lancaster University
OTHER
University of Southampton
OTHER
University College, London
OTHER
University of Aberdeen
OTHER
Responsible Party
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Locations
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University of Aberdeen
Aberdeen, UK, United Kingdom
Countries
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References
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Adam R, Lotankar Y, Sas C, Powell D, Martinez V, Green S, Cooper J, Bradbury K, Sive J, Hill DL. Understanding patterns of fatigue in health and disease: protocol for an ecological momentary assessment study using digital technologies. BMJ Open. 2024 May 27;14(5):e081416. doi: 10.1136/bmjopen-2023-081416.
Provided Documents
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Document Type: Informed Consent Form
Other Identifiers
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2-090-22
Identifier Type: -
Identifier Source: org_study_id
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