The True Recurrence Rate and Factors Predicting Recurrent Instability After Nonsurgical Management of Traumatic Primary Anterior Shoulder Dislocation: A Systematic Review
Bibliographic record
Abstract
PURPOSE: To (1) define the cumulative recurrence rate after primary anterior shoulder dislocation in Level I and II comparative studies and (2) to pool risk ratios for common risk factors to provide a clinically practical hierarchy of modifiable and nonmodifiable risk factors for recurrence. METHODS: Level I and II prognostic studies were identified using the electronic databases CINAHL, Embase, and MEDLINE from inception to December 2014. Included studies (n = 15) had recurrent dislocation as the main outcome, and a minimum 2-year follow-up. The cumulative odds ratio of prognostic factors was calculated where appropriate. Bias was assessed in each study using the Quality in Prognosis Studies (QUIPS) tool. RESULTS: The reported rate of recurrence ranged from 19% to 88% (pooled overall = 21%; pooled Level I only = 47%). The pooled time to recurrence was 10.8 months (standard deviation 0.42). Male sex (n = 6 studies) conferred a 2.68 (1.66-4.31; P < .001) and patient age <20 years (n = 4 studies) conferred a 12.76 (5.77-28.2; P < .001; vs >20 years) increased odds of recurrence. An associated greater tuberosity fracture (n = 7 studies) decreased the odds of recurrence by 3.8 times (2.94-5.00; P < .001). The quality of evidence was moderate for age, low for sex, and very low for all other prognostic variables. CONCLUSIONS: The pooled rate of recurrence after primary anterior shoulder instability was found to be 21% among moderate- to high-quality prognostic studies. Male sex and younger age predicted a significantly higher risk of recurrent instability (approaching 80%), whereas concurrent fracture of the greater tuberosity significantly decreased the risk of subsequent recurrent dislocation. However, considering the quality of available evidence for these predictors, there remains a clear need for further high-quality prospective studies. LEVEL OF EVIDENCE: Level II, systematic review of Level I and II prognostic studies.
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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 | 0.014 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".