Arthroscopic Treatment for Shoulder Instability with Glenoid Bone Loss Using Distal Tibia Allograft Augmentation: Two Year Outcomes
Bibliographic record
Abstract
Objectives: To analyse the clinico-radiologic outcomes of patients who underwent an all arthroscopic procedure to treat shoulder instability with glenoid bone loss using a distal tibial allograft; with a minimum 2 year follow-up. Methods: A retrospective chart review of prospectively collected data was completed for patients who underwent arthroscopic stabilization with Bankart repair and allograft bony augmentation of the glenoid; by the same surgeon. Western Ontario Shoulder Instability Index (WOSI), Disability of the Arm Shoulder and Hand (DASH), Veterans Rand - 12 and MARX questionnaires were completed pre and post-operatively. Radiological assessment was performed with radiographs and CT scans obtained pre-operatively and at approximately one year post surgery. Results: A total of 41 patients (29 males, 12 females) with a mean age of 26 ± 9 years were included. An excellent safety profile was observed, with no intraoperative complications, neurovascular injuries, adverse events, bleeding, or infections. At 2- year follow-up, there was statistically significant improvement of the WOSI score when compared preoperatively (preoperative=62.6 ± 17.06; at 2-year=22.96± 12.92; p<0.001). The mean pre-operative bone loss was 30.32% (SD ± 7.90). There were no cases of non- union or partial union. No resorption of the graft (grade 0) was seen in 42% patients, whereas 42% and 16% of patients had grade 1 and grade 2 resorption; respectively. There was 100% healing at the interface between allograft and native glenoid. The mean sagittal dimension of the remaining allograft post-operatively was 5.10 ± 2.27 mm in the patients with ≥50% resorption which indicates there was still bone graft present and there was no complete resorption. Mean post-operative external rotation for the population was also observed to near full. Conclusion: Arthroscopic stabilization with DTA augmentation has an excellent outcome at 2-year follow-up; long-term follow-up studies are necessary for better assessment of outcomes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".