Outcomes and Efficacy of the Bristow-Latarjet Technique in Shoulder Instability: A Case Series
Bibliographic record
Abstract
Objective: The glenohumeral joint is the most mobile in the human body because of its structural anatomy. This mobility renders the joint susceptible to dislocation, most commonly anterior dislocation. Various surgical options exist to address this condition, including open and arthroscopic procedures. The Bristow-Latarjet procedure is an open, non-anatomical repair technique used for anterior shoulder instability. This case series aimed to evaluate the clinical outcomes of the Bristow-Latarjet procedure in patients with anterior shoulder instability. Methods: In this case series, sixteen patients with anterior shoulder instability underwent the Bristow-Latarjet operation between January 2016 and November 2017. The follow-up period was 11.5 ± (range: 9–15) months. Clinical outcomes were evaluated using the Rowe score and the Western Ontario Shoulder Instability Index (WOSI), with complications recorded. Results: There was significant improvement in both outcome measures postoperatively. The preoperative Rowe score was 35.5 ± 12.26, which increased to 86.93 ± 4.67 postoperatively. Similarly, the WOSI score decreased from 62.95 ± 6.62 preoperatively to 17.43 ± 4.91 postoperatively. Three-fourths of the patients achieved an excellent Rowe score, 18.75% had a good score, and 6.25% had a poor score. Two patients experienced unexplained pain during activity, four patients exhibited a limitation in external rotation (without affecting daily activities), and one patient experienced re-dislocation. Conclusion: The Bristow-Latarjet procedure provides a viable treatment option for anterior shoulder instability, offering significant improvements in clinical outcome measures with a low rate of complications.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".