Handgrip Strength Features in Rheumatoid Arthritis Patients Assessed Using an Innovative Cylindrical-Shaped Device: Relationships With Demographic, Anthropometric and Clinical Variables

• Published in: Journal of medical systems Vol. 45; no. 11; p. 100
• Main Authors: Salaffi, Fausto, Carotti, Marina, Farah, Sonia, Ceccarelli, Luca, Di Carlo, Marco
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-11-2021; Springer Nature B.V
• Subjects: Age; Anthropometry; Arthritis; Arthritis, Rheumatoid; Body mass; Body mass index; Body measurements; Body size; Clinical Systems; Correlation coefficient; Correlation coefficients; Cross-Sectional Studies; Demographic variables; Demographics; Demography; Gender; Grasping; Grip force; Hand Strength; Health Informatics; Health Sciences; Humans; Medicine; Medicine & Public Health; Multivariate analysis; Patients; Rheumatoid arthritis; Statistics for Life Sciences; United States > US; Disease activity indices; Disability; Handgrip strength; Cylindrical-shaped dynamometer; Rheumatoid arthritis
• ISSN: 0148-5598; 1573-689X
• DOI: 10.1007/s10916-021-01778-9

To investigate the relationship between handgrip strength (HGs) features, evaluated with an innovative cylindrical-shaped grip device, and demographic, anthropometric and clinical variables, in patients with rheumatoid arthritis (RA). Consecutive RA patients were prospectively enrolled for this cross-sectional study. For each patient were collected demographic, anthropometric, clinical data related to disease activity. HGs was assessed in terms of area under the force–time curve (AUC-FeT), peak grip force and time to reach the curve plateau. The correlations between the variables were studied with the Spearman’s rho correlation coefficient. The receiver operating characteristic (ROC) curve analysis was used to test the discriminant accuracy of HGs features in identifying patients in moderate/high disease activity. A multivariate analysis was performed to estimate the contribution of covariates on the AUC-FeT. A significant correlation was found among AUC-FeT, age, Simplified Disease Activity Index (SDAI), Ultrasound-Clinical Arthritis Activity (US-CLARA) (all at
p
 < 0.0001), and body mass index (BMI) (
p
 = 0.0001). Any correlation was found between HGs and radiographic damage. The discriminatory power of AUC-FeT was good [area under-ROC curve = 0.810 (95% CI 0.746–0.864)]. Variables significantly associated with AUC-FeT in multivariate analysis were age (
p
 = 0.0006), BMI (
p
 = 0.012), gender (
p
 = 0.004), SDAI (
p
 = 0.047) and US-CLARA (
p
 = 0.023). HGs is negatively influenced by demographic (gender and age), anthropometric (BMI), and disease activity variables (SDAI and US-CLARA). These findings highlight the role of HGs in RA patients' functional impairment and disability.