Epidemiology of Primary Anterior Shoulder Dislocation Requiring Closed Reduction in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: There is a lack of high-quality population-based literature describing the epidemiology of primary anterior shoulder dislocation. PURPOSE: To (1) calculate the incidence density rate (IDR) of primary anterior shoulder dislocation requiring closed reduction (CR; "index event") in the general population and demographic subgroups, and (2) determine the rate of and risk factors for repeat shoulder CR. STUDY DESIGN: Cohort study (prognosis); Level of evidence, 2. METHODS: All patients who underwent shoulder CR by a physician in Ontario between April 2002 and September 2010 were identified with administrative databases. Exclusion criteria included age <16 and >70 years, posterior dislocation, and prior shoulder dislocation or surgery. Index event IDR was calculated for all populations/subgroups, and IDR comparisons were made. Repeat shoulder CR was sought until September 2012. Risk factors for repeat shoulder CR were identified with a Prentice, Williams, and Peterson proportional hazards model. RESULTS: There were 20,719 persons (median age, 35 years; 74.3% male) who underwent a shoulder CR after a primary anterior shoulder dislocation (23.1/100,000 person-years). The IDR was highest among young males (98.3/100,000 person-years). A total of 3940 (19%) patients underwent repeat shoulder CR after a median of 0.9 years, of which 41.7% were ≤20 years of age. Less than two-thirds of all first repeat shoulder CR events occurred within 2 years; in fact, 95% occurred within 5 years. The risk of repeat shoulder CR was lowest if the primary reduction had been performed by an orthopaedic surgeon (hazard ratio [HR], 0.76; 95% CI: 0.64, 0.90; P = .002) or was associated with a humeral tuberosity fracture (HR, 0.71; CI, 0.53, 0.95; P = .02). Older age (HR, 0.97; CI, 0.97, 0.98; P < .0001) and higher medical comorbidity score (HR, 0.92; CI, 0.87, 0.98; P = .009) were also protective. Risk was highest among males (HR, 1.26; CI, 1.16, 1.36; P < .0001) and patients from low-income neighborhoods (HR, 1.23; CI, 1.13, 1.34; P < .0001). CONCLUSION: Young male patients have the highest incidence of primary anterior shoulder dislocation requiring CR and the greatest risk of repeat shoulder CR. Patient, provider, and injury factors all influence repeat shoulder CR risk. A comprehensive understanding of the epidemiology of primary anterior shoulder dislocation will aid management decisions and injury prevention initiatives.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".