Open Versus Arthroscopic Latarjet for Recurrent Anterior Shoulder Instability: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: The open Latarjet (OL) procedure and arthroscopic Latarjet (AL) procedure are able to treat recurrent anterior shoulder instability (RASI) with high success rates. Purpose: To evaluate the clinical efficacy and postoperative revisions and complications between the OL and AL procedures in the treatment of RASI. Study Design: Systematic review; Level of evidence, 3. Methods: MEDLINE, Embase, and the Cochrane Library were searched to retrieve and include cohort studies comparing the OL and AL procedures for RASI. Clinical outcomes were compared, and results were reported as odds ratios (ORs) or mean differences (MDs) with 95% CIs. Results: Eleven clinical trials with 1217 patients were included. There were no differences between the procedures in pain score, Rowe score, Walch-Duplay score, external rotation, persistent apprehension, instability, recurrence, revisions attributed to recurrent instability, overall complications, wound infection, hematoma, graft complications, screw-related complications, or osteoarthritis. When compared with the OL procedure, the AL procedure had a significantly lower nonunion rate (OR, 9.92; 95% CI, 1.71 to 57.71; P = .01); however, the AL procedure had a longer operation time (MD, –24.49; 95% CI, –48.44 to –0.54; P = .05), lower Western Ontario Shoulder Instability Index score (MD, 97.27; 95% CI, 21.91 to 172.63; P = .01), higher revision rate (OR, 0.39; 95% CI, 0.16 to 0.95; P = .04), and greater screw deviation (MD, –6.41; 95% CI, –10.25 to –2.57; P = .001). Conclusion: For most outcome measures, no difference was seen between the OL and AL procedures. The AL procedure had a lower Western Ontario Shoulder Instability Index score and a higher revision rate and appeared to have a significant learning curve. However, the AL procedure resulted in a lower nonunion rate.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.025 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".