Arthroscopic Bankart Repair Versus Arthroscopic Latarjet for Anterior Shoulder Instability: A Matched-Pair Long-Term Follow-up Study
Bibliographic record
Abstract
Background: The Bankart and the Latarjet procedures are 2 of the most commonly utilized surgical techniques to treat anterior shoulder instability. However, the long-term outcomes after these procedures remain unclear, and there is not enough information regarding arthroscopic Latarjet. Purpose: To analyze long-term outcomes of patients with anterior glenohumeral instability managed with an arthroscopic Bankart or Latarjet procedure. Study Design: Cohort study; Level of evidence, 3. Methods: Patients who underwent an arthroscopic Latarjet were matched-paired in a 1:1 ratio with patients who underwent an arthroscopic Bankart procedure at a single institution between 2007 and 2012. Recurrence at the time of follow-up as well as intraoperative and postoperative complications were recorded and compared between the 2 groups. Postoperative status was assessed at the final follow-up using the Rowe score, the Western Ontario Shoulder Instability Index (WOSI), the Subjective Shoulder Value, and the return-to-sport rate. Results: A total of 80 patients, 40 patients in each group, were included (overall mean age, 26.5 ± 15.4 years). The mean follow-up was 13.2 years (range, 10-17 years). The recurrence rate was significantly higher in the Bankart group compared with the Latarjet group (35% vs 10%, respectively; P = .009). The mean estimate for the cumulative proportion of stable shoulders at 15-year follow-up was 64.4% in the Bankart group and 89.6% in the Latarjet group ( P = .008). Revision surgery because of instability was necessary in 8 (20%) patients in the Bankart group and 2 (5%) in the Latarjet group ( P = .41). There was no significant group difference in complication rate (15% in the Bankart group vs 17.5% in the Latarjet group; P = .48). The WOSI score was significantly better in patients treated with arthroscopic Latarjet ( P = .004). More than half of the patients were able to completely return to their previous sport (52.5%), with no significant difference between groups. Conclusion: Arthroscopic Latarjet was associated with a significantly lower recurrence rate and better postoperative WOSI score and sports activity level at long-term follow-up compared with arthroscopic Bankart, without any greater risk 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".