Does External Rotation Bracing for Anterior Shoulder Dislocation Actually Result in Reduction of the Labrum?
Bibliographic record
Abstract
BACKGROUND: External rotation (ER) bracing has been shown to improve labral reduction in cadaveric studies, but this has not translated to universal improvement in re-dislocation rates in clinical series. PURPOSE: To systematically review and critically appraise the literature that investigates how well the labrum is actually reduced by ER in patients who have had an anterior shoulder dislocation. STUDY DESIGN: Systematic review. METHODS: We conducted a systematic review of the literature using the online databases Medline, EMBASE, and the Cochrane Controlled Trial Register. Studies were included if they reported on the difference in labral reduction after ER and internal rotation bracing in patients who had a traumatic anterior shoulder dislocation. RESULTS: Of the 6 studies included, 5 assessed labral reduction on magnetic resonance imaging and 1 arthroscopically. Each study reported an overall improvement in labral reduction with ER, but anatomic reduction was not commonly achieved. This was despite the use of extreme positions that are unlikely to be well tolerated. CONCLUSION: External rotation results in anatomic reduction of the labrum in only 35% of cases. We postulate that failure to reduce the labrum may be a contraindication to ER bracing and propose further study to determine whether acute MRI could be used to help identify patients in whom ER achieves labral reduction in a comfortable position. This approach also has the advantage of avoiding the significant inconvenience of ER bracing in those in whom the labrum does not reduce and are therefore theoretically less likely to benefit. However, it is a novel strategy with significant resource implications and therefore warrants further study.
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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 | 0.013 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".