Both Open and Arthroscopic Latarjet Result in Excellent Outcomes and Low Recurrence Rates for Anterior Shoulder Instability
Bibliographic record
Abstract
Purpose The purpose of this study is to evaluate the patient‐reported outcomes of open Latarjet (OL) compared to arthroscopic Latarjet (AL) for anterior shoulder instability. Methods A retrospective review of patients who underwent either OL or AL for anterior shoulder instability between 2011 and 2019 was performed. Recurrent instability, visual analog scale (VAS) score, Shoulder Instability‐Return to Sport after Injury (SIRSI), Subjective Shoulder Value (SSV), Western Ontario Shoulder Instability (WOSI) score, patient satisfaction, willingness to undergo surgery again, and return to work/sport (RTW/RTS) were evaluated. A P value of < .05 was considered to be statistically significant. Results Our study included 102 patients in total; 72 patients treated with OL, and 30 treated with AL. There were no demographic differences between the two groups ( P > .05 for all). At final follow up (mean of 51.3 months), there was no difference between those that underwent OL or AL in the reported WOSI, VAS, VAS during sports, SSV, and SIRSI scores, nor in patient satisfaction, or whether they would undergo surgery again ( P > .05). Overall, there was no significant difference in the total rate of RTP (65% vs 60.9%; P = .74), or timing of RTP (8.1 months vs 7 months; P = .35). Additionally, there was no significant difference in the total rate of RTW (93.5% vs 95.5%; P = .75). Overall, 3 patients in the OL group and 2 patients in the AL group had recurrent instability events (6.9% vs 6.7%; P = .96), with no significant difference in the rate of recurrent dislocation (4.2% vs 3.3%; P = .84). Conclusion In patients with anterior shoulder instability, both the OL and AL are reliable treatment options, with a low rate of recurrent instability, and similar patient‐reported 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".