Arthroscopic Treatment of Posterior Shoulder Instability
Bibliographic record
Abstract
BACKGROUND: Posterior shoulder instability is a relatively rare condition and a surgical challenge. Arthroscopic techniques have allowed for a potential improvement as well as diagnosis and management of this condition. PURPOSE: To evaluate the outcomes of arthroscopic posterior shoulder stabilization and to evaluate preoperative and intraoperative variables as predictors of success. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: Thirty-three consecutive patients with a mean age of 25 years (range, 19-34 years) who underwent posterior arthroscopic shoulder stabilization with suture anchors (mean, 3 anchors) or suture capsulolabral plication (mean, 5.3 stitches) or both were reviewed at a mean follow-up of 39.1 months (range, 22-60 months). Shoulder outcomes rating scores were determined using the American Shoulder and Elbow Surgeons Rating Scale, the Western Ontario Shoulder Instability Index, the Subjective Patient Shoulder Evaluation, and the Single Assessment Numeric Evaluation. RESULTS: There were 7 failures: 4 for recurrent instability and 3 for symptoms of pain. Overall, outcomes scores demonstrated mean values of the American Shoulder and Elbow Surgeons Rating Scale of 94.6, Subjective Patient Shoulder Evaluation of 20.0, Western Ontario Shoulder Instability Index of 389.4 (81.5% of normal), and Single Assessment Numeric Evaluation of 87.5. Patients with voluntary instability demonstrated worse outcomes (P = .025), and those with prior surgery of the shoulder also did worse (P = .02). CONCLUSION: Arthroscopic treatment of posterior shoulder instability is an effective means to improve symptoms associated with recurrent posterior subluxation of the shoulder. It can provide predictable success in the setting of unidirectional, nonvoluntary posterior instability without prior surgery.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".