Background: Symptoms in patients with rheumatoid arthritis (RA) are potentially influenced by exercise load and meteorological change, and often vary from day to day, especially in unstable condition of RA. Patients with RA not infrequently experience worsening of joint symptoms when the load on the joint, such as walking and doing housework, exceeds a moderate range. However, the worsening of joint symptoms is not often observed in the midst of the loading of the joint, but often becomes apparent after a few hours or days. The authors have been working on visualizing patients’ physical and mental condition using digital devices [1,2].

Objectives: To develop an internet of things (IoT) systems that collects patients’ daily condition and activity/sleep levels using smartphones and wearable devices, and to elucidate the relationship between disease activity and smartwatch-acquired daily sensing data including steps, heart rate and sleep in RA.

Methods: Patients with RA from three sites (Keio University Hospital, NHO Tokyo Medical Center and Kawasaki Municipal Hospital) participated in the study. A smartphone (iPhone 12) and a wrist-worn smartwatch (Fitbit Sense 2) were lent to each patient. A mobile app was developed and installed into the smartphones to collect patients’ daily PRO including patient-pain-visual analogue scale (Pt-P-VAS), pt-general-VAS (Pt-G-VAS), etc. Patients were requested to enter PRO into the app at least once a week at home. Also, rheumatologists’ assessment including doctor-general-VAS (Dr-G-VAS) and the smartwatch data including steps/metabolic equivalents (METs), heart rate and sleep status were collected from the same subject. Patients visited the clinic, had blood drawn and were evaluated by the physicians every 4 weeks; patients were observed for a total of 12 weeks. The wearable device measurements remained blinded to the rheumatologists during the study period.

Results: A total of 120 patients (18 men; 102 women) were enrolled. At baseline, mean age was 54.9 years; mean disease duration was 9.5 years; mean SDAI was 10; mean DAS28-ESR was 3.5.

More steps/METs were associated with fewer DAS28-ESR (95%CI -0.53 to -0.13, P=0.002)/ SDAI (-0.47 to -0.054, P=0.016)/ CDAI (-0.46 to -0.047, P=0.018)/ HAQ-DI (-0.29 to -0.20, P<0.001)/ Dr-G-VAS (-0.49 to -0.088, P=0.007).

In addition, increased heart rate during sleep was associated with increased CDAI (95%CI 0.029 to 0.41, P=0.025)/ SDAI (0.028 to 0.41, P=0.026)/ MMP-3 (0.051 to 0.53, P=0.020). Moreover, an increase in deep sleep ratio was associated with a decrease in CRP (95%CI -0.44 to -0.15, P<0.001). Higher sleep efficiency (the ratio between the time a person spends asleep and the total time dedicated to sleep) associated with lower ESR (95%CI -0.36 to -0.040, P=0.015).

Conclusion: An IoT system that collects patients’ daily physical condition and activity level was successfully developed. Patients with poor RA status were less active, and inflammatory status was associated with sleep quality. The sensing data can provide an estimate of the RA patient’s condition and may help monitor the patient at home.

REFERENCES: [1] Izumi K, Moriwaki D, Toda T, et al. AB0145 SMARTPHONE- AND SMARTWATCH-ACQUIRED DAILY STEPS, ACTIVITY, AND BAROMETRIC PRESSURES ASSOCIATED WITH SUBJECTIVE MEASURES OF RHEUMATOID ARTHRITIS: A PROSPECTIVE STUDY FOR RA DIGITAL PHENOTYPING. Ann Rheum Dis 2021;80:1099-1100.

[2] Izumi K, Minato K, Shiga K, et al. Unobtrusive Sensing Technology for Quantifying Stress and Well-Being Using Pulse, Speech, Body Motion, and Electrodermal Data in a Workplace Setting: Study Concept and Design. Front Psychiatry 2021;12:611243.

Acknowledgements: This research was supported by AMED.

Disclosure of Interests: Keisuke Izumi Asahi Kasei, Chugai, Abbvie, Eisai, Gilead Sciences, TechDoctor, Inc., TechDoctor, Inc., Asahi Kasei, Abbvie, Misako Higashida-Konishi: None declared, Shuntaro Saito: None declared, Satoshi Hama: None declared, Kazuoto Hiramoto: None declared, Nobuhiko Kajio: None declared, Yasushi Kondo: None declared, Kanata Suzuki Fujitsu, Ltd., Toshikazu Fukami TechDoctor, Inc., Kazumichi Minato TechDoctor, Inc., TechDoctor, Inc., Yoshimitsu Aoki: None declared, Hiroaki Taguchi: None declared, Yuko Kaneko AbbVie, Asahikasei, Astellas, Ayumi, Boehringer Ingelheim, Bristol-Myers Squibb, Chugai, Eisai, Eli Lilly, Hisamitsu, Jansen, Kissei, Pfizer, Sanofi, Takeda, Tanabe-Mitsubishi and UCB.