Long-term outcomes of the Latarjet procedure in a North American population
Bibliographic record
Abstract
Background: Anterior glenohumeral instability often necessitates surgical intervention to prevent recurrence. The open Latarjet procedure is a technique that transfers the coracoid process and conjoined tendon to the anterior glenoid for a triple blocking effect. Originally popularized in Europe, this procedure has become increasingly performed in North America. This study aims to present the long-term outcomes of the largest series of Latarjet procedures performed in North America. Methods: Patients from two surgeons at a single site who underwent the Latarjet procedure between January 2003 and January 2023 were invited to complete a digital survey capturing their clinical history and perspectives. One hundred eighteen patients completed patient-reported outcome measures including Single Assessment Numeric Evaluation and Western Ontario Shoulder Instability Index and responded to questions about dislocations, prior and additional surgery, and instability. Results: Overall, 94.07% of respondents required no additional shoulder surgery, 94.92% reported no dislocations, and 83.90% reported no slipping. The mean Single Assessment Numeric Evaluation and Western Ontario Shoulder Instability Index scores were 84.01 and 21.01, respectively. Discussion: Short-, mid-, and long-term results indicate positive clinical outcomes. The long-term data suggest that these benefits are durable, and the Latarjet procedure should be considered as a viable and reliable treatment option for anterior glenohumeral instability. This study indicates that long-term Latarjet clinical and patient outcomes are consistent and favorable in a North American patient population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".