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In patients with rheumatoid arthritis (RA), smartphone-based assessments of physical function have the potential to capture and quantify meaningful objective clinical information remotely, according to results of a research report published in Digital Biomarkers.
Researchers sought to examine the feasibility of evaluating iPhone sensor data obtained remotely via a mobile software application to collect meaningful information on functional ability among patients with RA.
The PARADE study was conducted in the United States between July and November 2016. Researchers used 2 objective, active tests for the study participants: a wrist joint motion test and a walk test, both of which were performed remotely, without any medical supervision. Gyroscope and accelerometer time-series data were captured while participants performed the tasks. Quality of life of participants was evaluated using the 5-level version of the EuroQol, 5 dimensions (EQ-5D-5L) questionnaire, which included questions on mobility, pain/discomfort, self-care, usual activities, and anxiety/depression.
A total of 399 individuals participated in the study and were invited to report on various symptoms each week, using their iPhone, for 12 weeks.
Wrist joint motion sensor data were obtained at weeks 1 and 12. Participants received a short video in which they were asked to sit down and place their forearm at the edge of a table, palm facing up, and holding the iPhone in their hand for 10 seconds — first with the right hand and then with the left hand. Participants were asked to flex and extend their wrist joint to its maximum range of motion (ROM). However, participants who reported having severe wrist joint or hand arthritis were asked not to attempt this task.
The walk task included 3 segments, each of which was performed with the iPhone in participants’ pockets. Walk test data were collected on a weekly basis for the duration of the study. Segment 1 of the walk test included the participant walking up to 10 steps in a straight line for 10 seconds; in segment 2, the participant turned around and stood still for 10 seconds; and in segment 3, the participant walked up to 10 steps back for 10 seconds.
Overall, 646 wrist joint motion samples were collected, with 289 (45%) considered to be of high quality. Regarding the walk test, data collected included 2583 samples, of which 651 (25%) were of high quality. Additional evaluation of the high-quality data revealed associations between reduced mobility and increased symptom severity.
According to one-way analysis of variance (ANOVA) testing, statistically significant differences were observed in wrist joint ROM between the 220 participants with light to moderate wrist pain and the 36 participants with severe wrist pain (P <.001). Significant differences in average step times were also observed between the group of participants with slight difficulties and those with moderate difficulties walking (P <.03).
A major limitation of the current study was the fact the variability reported in the sensor data, with objective activity tasks performed, as expected, in 45% of wrist motion data samples and in 25% of walk data samples.
According to the researchers, “Further investigation and improvement to data acquisition schemes would be needed to confirm these observations. This includes prospective testing and changes to the design of the objective tasks to reduce variability and therefore increase data quality along with output measures’ accuracy.”
Disclosure: This study was supported by GlaxoSmithKline plc, London, UK. Please see the original reference for a full list of authors’ disclosure.
Reference
Hamy V, Garcia-Gancedo L, Pollard A, et al. Developing smartphone-based objective assessments of physical function in rheumatoid arthritis patients: the PARADE study. Digit Biomark. 2020;4(1):26-43. doi:10.1159/000506860
