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  1. R. Barnett1,2,
  2. S. Ng3,
  3. S. Jones1,
  4. M. Young1,
  5. R. Sengupta1,2
  1. 1University of Bath, Bath, United Kingdom
  2. 2RNHRD, Bath, United Kingdom
  3. 3White Swan, Exeter, United Kingdom


Background: Axial spondyloarthritis (axSpA) is a chronic inflammatory disease, characterised by fluctuating periods of flare and remission. Flare is a multidimensional change of disease state; whereby flare definitions have previously been formulated using validated composite indices, or through qualitative retrospective investigation of flare states. Smartphone technologies for tracking disease symptoms provide unique, daily insights into self-reported individual flare experience, and may present an opportunity to gain a more complete understanding of flare burden and symptom patterns.

Objectives: To assess frequency and characteristics of axSpA flares, utilising data collected in the uMotif symptom tracking app.

Methods: Patients with axSpA attending the Royal National Hospital for Rheumatic Diseases in Bath were invited to participate. Through the uMotif app, patients were sent daily reminders to log flare, pain, fatigue, sleep, recommended exercise, mood and stress using 5-point Likert scales, in addition to optional variables such as smoking and menstrual cycle. Self-reported periods of flare were identified. For each patient reporting flare within the study period, a mean ‘flare’ and ‘non-flare’ score was calculated for each variable. Paired t-tests were conducted for each variable, to investigate which variables correlate with flare status.

Results: Between 5th April 2018 and 8th March 2019, 174 patients consented for research and logged a mean of 99.73 (SD 99.97, range 1 - 323 days) days of data. 136/174 (78%) patients recorded at least 1 flare, with 1330 flares recorded in total. For patients reporting at least 1 flare, each flare lasted a mean of 2.20 days (SD 2.53 days, range 1 – 33 days), with a mean frequency of once every 45.19 days (SD 53.06, range 3.2 -314 days). Significant relationships were identified between flare status and uMotif scores (Table 1).

Table 1.

Paired t-tests: flare vs. non-flare scores for each variable

Conclusion: These findings demonstrate significant relationships between a variety of patient-reported symptoms and flare, including variables that to our knowledge, have not yet been explored in axSpA. Small estimated differences were found between scores for ‘flare’ versus ‘no-flare’. Further work is needed to characterise fluctuating flare/no-flare patterns of individuals tracking daily symptoms in the uMotif app. In future research, it will be important to determine whether there is a chronological pattern of variables during the pre-flare period that can predict a flare. Greater understanding of such patterns may allow identification of the optimal timing of intervention to prevent a period of flare and improve quality of life for patients with axSpA.

Acknowledgments: We thank UCB for funding use of the uMotif application.

Disclosure of Interests: Rosie Barnett: None declared, Stanley Ng: None declared, Simon Jones: None declared, Matthew Young: None declared, Raj Sengupta Grant/research support from: Research grants from UCB, Pfizer, Abbvie and Novartis, Speakers bureau: Received honoraria for giving talks from Abbvie, Biogen, UCB, Novartis, Pfizer

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