Anterior and posterior glenoid bone augmentation options for shoulder instability: state of the art
Bibliographic record
Abstract
Bony lesions are highly prevalent in anterior shoulder instability and can be a significant cause of failure of stabilisation procedures if they are not adequately addressed. The glenoid track concept describes the dynamic interaction between the humeral head and glenoid defects in anterior shoulder instability. It has been beneficial for understanding the role played by bone defects in this entity. As a consequence, the popularity of glenoid augmentation procedures aimed to treat anterior glenoid bone defects; reconstructing the anatomy of the glenohumeral joint has risen sharply in the last decade. Although bone defects are less common in posterior instability, posterior bone block procedures can be indicated to treat not only posterior bony lesions, attritional posterior glenoid erosion or dysplasia but also normal or retroverted glenoids to provide an extended glenoid surface to increase the glenohumeral stability. The purpose of this review was to analyse the rationale, current indications and results of surgical techniques aimed to augment the glenoid surface in patients diagnosed of either anterior or posterior instability by assessing a thorough review of modern literature. Classical techniques such as Latarjet or free bone block procedures have proven to be effective in augmenting the glenoid surface and consequently achieving adequate shoulder stability with good clinical outcomes and early return to athletic activity. Innovations in surgical techniques have permitted to perform these procedures arthroscopically. Arthroscopy provides the theoretical advantages of lower morbidity and faster recovery, as well as the identification and treatment of concomitant pathologies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".