Functional Hand-Based Splint in the Treatment of Metacarpal Fractures
Bibliographic record
Abstract
Background: Post-treatment stiffness remains a significant hurdle following treatment for displaced or minimally displaced metacarpal fractures. Treatment goals should focus on a stable and acceptable reduction, minimal patient morbidity, and optimal mobility. Methods: A retrospective review of all non-operative metacarpal fractures over a five-month period at a tertiary center hand clinic treated with a hand-based splint were reviewed for radiologic and clinical stability. The splint allowed metacarpophalngeal joint, interphalangeal joint, and radiocarpal joint motion. Data collected included age, handedness, type and location of fracture, occupation, and ability to continue working. Radiologic images were reviewed by a radiologist not otherwise involved in patient care. Results: Thirty-three patients were reviewed with a total of 39 fractures of the second, third, fourth, and fifth metacarpals. Nine patients had nondominant hand fractures while 24 were dominant hand injuries. Twenty out of 24 patients employed pre-injury were able to continue working without missing any days. Three patients were lost to the final follow-up. The average splint duration was 24 days. Twenty-seven of 30 patients showed no change in alignment from start of splinting to end, while three showed some change but remained within non-operative criteria. Conclusion: A hand-based functional splint for metacarpal fractures allows for excellent maintenance of fracture reduction, early or immediate return to pre-injury activities, low patient morbidity, and maintains functional motion throughout treatment. It can be applied to any non-operative fracture of the second through the fifth metacarpal.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".