Early functional mobilization for non-operative treatment of simple elbow dislocations: a systematic review
Bibliographic record
Abstract
Purpose: This systematic review aims to elucidate a non-operative rehabilitation program that optimizes recovery based on published approaches and outcomes. Methods: Searches of four databases from inception to 1 January 2020 were performed to identify clinical studies addressing the non-operative management of simple elbow dislocations. Results: Of 2435 studies that were eligible for title screen, 15 studies satisfied inclusion criteria. Three randomized control studies demonstrated that early mobilization expedited the return of range of motion, function and return to work or activities, however, resulted in increased pain within the six-week rehabilitation period compared to Plaster of Paris casting for 21 days. Patients returned to work sooner after early mobilization (10 vs. 18 days; p = 0.02) compared to Plaster of Paris casting. In all studies, early mobilization resulted in similar re-dislocation rates of 1.3% (3/237) versus 2.2% (12/549) in those with Plaster of Paris casting as well as lower incidence of heterotopic ossification (36% vs. 54%). No significant differences between rehabilitation protocols were determined; however, the large majority of recent papers utilized rehabilitation protocols. Conclusion: Early mobilization of simple elbow dislocations results in early return of Range-of-Motion, function and return to work with no increase in complication rates; however, increased pain during the rehabilitation period.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".