Mid-term Functional Outcomes of Open Congruent Arc Latarjet for Recurrent Anterior Shoulder Instability: A Retrospective Cohort Study
Bibliographic record
Abstract
Introduction: Recurrent anterior shoulder instability with significant glenoid bone loss is associated with high failure after isolated soft-tissue repair. The open Latarjet procedure with congruent arc modification improves graft coverage and glenoid arc restoration, but mid-term clinical data are limited. Materials and Methods: This retrospective cohort included patients who underwent open Latarjet with congruent arc modification between January 2015 and December 2020. Eligibility criteria were ≥3 anterior dislocations, ≥15% glenoid bone loss, and ≥24 months of follow-up. Functional outcomes (Western Ontario Shoulder Instability Index [WOSI], Rowe), range of motion, complications, and graft union on computed tomography (CT) were assessed. Kaplan-Meier survival analysis estimated recurrence-free survival. Results: A total of 80 patients (62 males, 18 females; mean age 28.5 ± 6.4 years) were analyzed with a mean follow-up of 4.5 ± 1.2 years. WOSI improved from 46.7 ± 12.3 to 79.4 ± 15.8 (P < 0.001), and Rowe from 32.5 ± 9.6 to 85.6 ± 10.7 (P < 0.001), both exceeding minimal clinically important difference thresholds. Forward flexion (+15°) and abduction (+20°) improved significantly, whereas external rotation showed a mild, non-significant reduction (-10°, P = 0.079). Complications occurred in 12.5%, mainly graft non-union (5%). CT confirmed graft union in 95%. Kaplan-Meier analysis showed 97.5% recurrence-free survival at 5 years. Conclusion: Open Latarjet with congruent arc modification provides clinically meaningful functional improvement, reliable graft union, and durable mid-term stability in recurrent anterior instability with glenoid bone loss.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".