Objective: The aim was to analyse the accuracy of a hand dynamometer connected to a smartphone to assess RA disease activity through the measurement of handgrip strength (HGS).
Methods: Eighty-two RA patients participated in this prospective study. Three types of HGS were assessed: power (Po), pinch (Pi) and tripod (T). An interactive mobile application was developed to capture grip measures. A unilinear regression analysis between HGS and DAS28 was performed. A multivariate regression analysis to identify independent variables related to HGS was also conducted.
Results: Sixty-three patients (76.8%) were female. Mean age was 61.3 years. At baseline, a negative correlation between the three HGS measures and DAS28 score was found, as follows: Po, r = -0.65 (95% CI: -0.76, -0.51, P < 0.001); Pi, r= -0.42 (95% CI: -0.59, -0.23, P < 0.001); and T, r = -0.47 (95% CI: -0.63, -0.29, P < 0.001). In a longitudinal analysis of 32 patients, a negative correlation between ΔPo grip and ΔDAS28 was found (r = -0.76, 95% CI: -0.88, -0.56). Po grip was independently correlated with male sex (95% CI: 1.49, 4.14, P = 0.002), whereas variables inversely correlated with Po grip were disease duration (95% CI: -2.71, -1.34, P = 0.03), patient global assessment (95% CI: -2.41, -1.1, P < 0.001) and CRP level (95% CI: -3.56, -1.08, P < 0.001).
Conclusion: HGS assessed by a hand dynamometer connected to a smartphone represents an innovative health technology solution that could prompt the self-assessment of RA disease activity in an outpatient setting.
Keywords: biomedical technology; hand strength; rheumatoid arthritis; telemedicine.
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