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Abstract
Background. Axial spondyloarthritis (axSpA) is a chronic inflammatory disease primarily affecting the spine and sacroiliac joints, characterised by fluctuating periods of flare and remission. Management is mainly based on patient-reported symptoms and outcome measures collected at follow-up appointments, which may be subject to recall bias. Smartphone technologies for monitoring disease symptoms provide an opportunity to gain a more complete understanding of disease burden and symptom patterns and may facilitate optimisation and personalisation of axSpA management.
Aims. To analyse data collected in the uMotif symptom tracking app and assess correlations between axSpA symptoms.
Methods. Patients with axSpA attending the Royal National Hospital for Rheumatic Diseases in Bath were invited to participate in the study. Through the uMotif app, patients were sent daily reminders to log pain, fatigue, sleep, recommended exercise, mood and stress using 5-point likert scales. Between 05/04/18 and 04/03/19, 236 patients registered on the app and logged a mean of 85.1 (SD=91.8) days of data (range=1 - 317 days). For each patient, a mean score was calculated for each variable over their total logging period. Spearman rank correlation coefficients were used to evaluate inter-variable correlations.
Results. Significant correlations were identified between uMotif variables, including mood and stress, pain and fatigue; in addition to exercise and sleep, and exercise and mood - supporting existing evidence regarding exercise implementation in axSpA.
Conclusions. These findings demonstrate a clear relationship between a variety of patient-reported symptoms in axSpA. In future research, it will be important to determine whether there is a chronological pattern within an individual or combination of variables that could predict a flare. Earlier intervention to ameliorate these symptoms may ultimately reduce flare frequency, duration and intensity, and greatly improve the quality of life for patients with axSpA.
Aims. To analyse data collected in the uMotif symptom tracking app and assess correlations between axSpA symptoms.
Methods. Patients with axSpA attending the Royal National Hospital for Rheumatic Diseases in Bath were invited to participate in the study. Through the uMotif app, patients were sent daily reminders to log pain, fatigue, sleep, recommended exercise, mood and stress using 5-point likert scales. Between 05/04/18 and 04/03/19, 236 patients registered on the app and logged a mean of 85.1 (SD=91.8) days of data (range=1 - 317 days). For each patient, a mean score was calculated for each variable over their total logging period. Spearman rank correlation coefficients were used to evaluate inter-variable correlations.
Results. Significant correlations were identified between uMotif variables, including mood and stress, pain and fatigue; in addition to exercise and sleep, and exercise and mood - supporting existing evidence regarding exercise implementation in axSpA.
Conclusions. These findings demonstrate a clear relationship between a variety of patient-reported symptoms in axSpA. In future research, it will be important to determine whether there is a chronological pattern within an individual or combination of variables that could predict a flare. Earlier intervention to ameliorate these symptoms may ultimately reduce flare frequency, duration and intensity, and greatly improve the quality of life for patients with axSpA.
Original language | English |
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Publication status | Published - 26 Sept 2019 |
Event | BRITSpA 5th Annual Scientific Meeting - Hilton Birmingham Metropole, Birmingham, UK United Kingdom Duration: 25 Sept 2019 → 26 Sept 2019 |
Conference
Conference | BRITSpA 5th Annual Scientific Meeting |
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Country/Territory | UK United Kingdom |
City | Birmingham |
Period | 25/09/19 → 26/09/19 |
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Dive into the research topics of 'Association of self-reported pain, fatigue, sleep, exercise, mood and stress in spondyloarthritis: initial analyses from the Project Nightingale study'. Together they form a unique fingerprint.Projects
- 1 Finished
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Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)
Cosker, D. (PI), Bilzon, J. (CoI), Campbell, N. (CoI), Cazzola, D. (CoI), Colyer, S. (CoI), Fincham Haines, T. (CoI), Hall, P. (CoI), Kim, K. I. (CoI), Lutteroth, C. (CoI), McGuigan, P. (CoI), O'Neill, E. (CoI), Richardt, C. (CoI), Salo, A. (CoI), Seminati, E. (CoI), Tabor, A. (CoI) & Yang, Y. (CoI)
Engineering and Physical Sciences Research Council
1/09/15 → 28/02/21
Project: Research council