The effects of hand splinting in patients with early-stage thumb carpometacarpal joint osteoarthritis: a randomized, controlled study
Bibliographic record
Abstract
Background/aim: Evidence for the effectiveness of splinting in thumb carpometacarpal osteoarthritis is limited. We aimed to evaluate the effects of a prefabricated carpometacarpal metacarpophalangeal immobilization splint on pain, hand function, and hand strength in patients with early-stage thumb carpometacarpal osteoarthritis. Materials and methods: Sixty-three hands with stage 1 or 2 thumb carpometacarpal osteoarthritis were enrolled in the study. The nonsplint group received oral information about how to accommodate daily activities. The splint group was given a prefabricated carpometacarpal metacarpophalangeal immobilization splint for 6 weeks. Pain was evaluated using the Australian/Canadian Osteoarthritis Hand Index (AUSCAN). Hand functions were evaluated using the AUSCAN and the Quick Disabilities of Arm, Shoulder and Hand (Q-DASH) questionnaire. Grip and pinch strengths were measured using a hydraulic dynamometer and a hydraulic pinch gauge. Results: The AUSCAN pain, stiffness, function, total scores, and Q-DASH scores were significantly decreased in the splint group compared to the nonsplint group. Significant increments in grip and pinch strengths were detected in the splint group compared to the nonsplint group. Conclusion: The prefabricated carpometacarpal metacarpophalangeal immobilization splint is effective in improving pain, hand function, and hand strength in patients with thumb carpometacarpal osteoarthritis.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".