Association of Sarcopenia with Pain and Disability in Hand Osteoarthritis: A Retrospective, Cross-Sectional, Single-Center Study
Bibliographic record
Abstract
BACKGROUND/AIMS: Sarcopenia is known to worsen clinical outcomes in osteoarthritis, particularly in weight-bearing joints, yet its relationship with symptom burden in hand osteoarthritis has not been well established. This study explored the relationship between sarcopenia, hand pain, and functional status in patients with hand osteoarthritis. MATERIALS AND METHODS: A retrospective analysis was conducted on 1139 patients aged ≥40 years with radiographically confirmed hand osteoarthritis. Sarcopenia was defined as the ratio of muscle mass to body mass index, measured via bioelectrical impedance analysis. Hand pain and function were assessed using the Australian/Canadian Osteoarthritis Hand Index, and the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaires. Sex-specific multivariable linear regression models were constructed, adjusting for demographic and lifestyle covariates. RESULTS: In males, lower appendicular skeletal muscle mass/body mass index was significantly associated with higher DASH scores (estimate: -10.664, P = .006). A significant association with higher Australian/Canadian Osteoarthritis Hand Index scores was also observed (estimate: -26.236, P = .030). Lower upper-extremity muscle mass/body mass index was likewise associated with higher DASH scores in males (estimate: -41.074, P = .013). In females, none of the associations reached statistical significance. CONCLUSION: These findings suggest that sarcopenia contributes to increased pain and disability in hand osteoarthritis, highlighting the clinical importance of preserving muscle mass in its management. Cite this article as: Lee H, Lee S-I, Cheon Y-H, et al. Association of sarcopenia with pain and disability in hand osteoarthritis: a retrospective, cross-sectional, single-center study. Arch Rheumatol. 2025;40(4):492-498.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".