Clinical Outcomes Following Revision Shoulder Arthroscopic Capsulolabral Stabilization
Bibliographic record
Abstract
Objectives: The purpose of this study was to assess clinical outcomes in patients following revision shoulder arthroscopic capsulolabral stabilization. The hypothesis was that revision arthroscopic stabilization would offer predictable clinical outcomes in appropriately selected patients. Methods: Sixty-two patients (63 shoulders) with failure of primary instability repairs were treated with revision arthroscopic shoulder stabilization at a mean follow-up of 46.9 ± 16.8 months (range, 15-78). Forty-six male patients and 16 females with a mean age of 23.2 ± 6.9 years (range, 14.7 - 47.2) met the inclusion criteria for the study. Revision arthroscopic stabilization was indicated in patients with recurrent instability with limited glenoid bone loss. Clinical outcomes were evaluated using validated patient reported outcome questionnaires including the American Shoulder and Elbow Surgeons score, Simple Shoulder Test, visual analog pain scale and Western Ontario Shoulder Instability Index. In addition, patients were queried for recurrent instability events (subluxation or dislocation) or revision surgery. Results: At final follow-up, the mean post-operative Western Ontario Shoulder Instability normalized score was 80.1 (range, 15.0 - 100). There were clinically significant improvements in American Shoulder and Elbow Surgeons scores from 63.7 pre-operatively to 85.1 post-operatively (P < 0.001), Simple Shoulder Test scores from 61.8 pre-operatively to 90.9 post-operatively (P < 0.001), and VAS pain scores from 2.89 pre-operatively to 0.81 post-operatively (P < 0.001). Recurrent instability occurred in 12 shoulders (19.0 %), with number of prior surgeries and hyperlaxity found to be significant risk factor for failure (P < 0.001 and P = 0.04, respectively). Conclusion: Arthroscopic revision stabilization of the shoulder can result in satisfactory outcomes in patients who have failed previous capsulolabral repair. Increased number of prior surgeries and hyperlaxity are predictive of poor outcome. Longer-term studies are required to determine whether similar results are maintained over time, and to provide guidance on focused clinical indications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".