Wearable devices detect physiological changes that precede and are associated with symptomatic and inflammatory rheumatoid arthritis flares.

Physiological parameters are altered in rheumatoid arthritis (RA). We evaluated whether changes in physiological metrics, collected from wearable devices, identify and precede the development of both symptomatic and inflammatory RA flares. Participants with RA answered daily disease activity surveys and provided laboratory assessments of inflammatory activity. They wore an Apple Watch (n = 35), Fitbit (n = 17), or Oura Ring (n = 3) collecting heart rate (HR), resting heart rate (RHR), heart rate variability (HRV), and steps. Linear mixed effect models were used to associate HR, RHR and steps with flare and remission periods. Cosinor mixed effect models assessed circadian features of HRV. Mixed effect logistic regression models evaluated changes in physiological metrics prior to the onset of flares. The study enrolled 53 participants (88.7% female) with a mean age of 51.1 (SD 15.2) years. Each contributed a mean of 105 (SD 97) days of data. Mean steps were lower, while mean nighttime HR was higher during symptomatic periods, compared to periods of symptomatic remission. Means daily HR, daytime HR, nighttime HR, and RHR were higher during periods of inflammatory flares, compared to inflammatory remission. Circadian features of HRV differentiated inflammatory and symptomatic flares from remission. All metrics were altered up to 4 weeks prior to inflammatory and symptomatic flare development. This suggests the potential use of wearable devices for disease monitoring and flare prediction.