Handgrip Strength Features in Rheumatoid Arthritis Patients Assessed Using an Innovative Cylindrical-Shaped Device: Relationships With Demographic, Anthropometric and Clinical Variables.
Fausto SalaffiMarina CarottiSonia FarahLuca CeccarelliMarco Di CarloPublished in: Journal of medical systems (2021)
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.
Keyphrases
- disease activity
- rheumatoid arthritis patients
- rheumatoid arthritis
- systemic lupus erythematosus
- ankylosing spondylitis
- body mass index
- end stage renal disease
- juvenile idiopathic arthritis
- chronic kidney disease
- newly diagnosed
- ejection fraction
- magnetic resonance imaging
- mental health
- peritoneal dialysis
- weight loss
- physical activity
- deep learning
- interstitial lung disease