Nonoperative Management of Posterior Shoulder Instability: What Are the Long-Term Clinical Outcomes?
Bibliographic record
Abstract
Objective: To report the injury characteristics, radiographic findings, and long-term outcomes of nonoperative management for posterior shoulder instability (PSI). Design: A retrospective review of 143 patients with PSI using a large geographic database. Setting: Single county between January 1994 and July 2012. Patients: A clinical history and diagnosis of PSI, one confirmatory imaging study to support the diagnosis, and a minimum of 5 years follow-up were required for inclusion. Patients with seizure disorders, anterior-only instability, multidirectional instability, and superior labrum from anterior to posterior diagnosis were excluded. Interventions: Patients with PSI were managed nonoperatively or operatively. Main Outcome Measures: Pain, recurrent instability, and progression into glenohumeral osteoarthritis at long-term follow-up. Results: One hundred fifteen patients were identified. Thirty-seven (32%) underwent nonoperative management. Twenty (54%) patients were diagnosed with posterior subluxation, 3 (8%) with a single dislocation, and 7 (19%) with multiple dislocations. Symptomatic progression of glenohumeral arthritis was observed in 8% (3) of patients. Pain improved in 46% (17) of patients and worsened in 19% (7). Recurrent instability and progression to osteoarthritis occurred in 15% (3/20) of patients with a traumatic instability event compared with 0% of atraumatic patients after nonoperative management ( P = 0.234). Pain at follow-up was more common in nonoperative than operative patients ( P = 0.017). Conclusions: Nonoperative management is a viable option for many patients with posterior shoulder instability; however, many may continue to have posterior shoulder pain.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".