Arthroscopic iliac crest bone grafting in recurrent anterior shoulder instability: minimum 5‐year clinical and radiologic follow‐up
Bibliographic record
Abstract
PURPOSE: To investigate the clinical and radiologic mid- to long-term results of arthroscopic iliac crest bone-grafting for anatomic glenoid reconstruction in patients with recurrent anterior shoulder instability. METHODS: Seventeen patients were evaluated after a minimum follow-up of 5 years. Clinical [range of motion, subscapularis tests, apprehension sign, Subjective Shoulder Value (SSV), Constant Score (CS), Rowe Score (RS), Walch Duplay Score (WD), Western Ontario Shoulder Instability Index (WOSI)], and radiologic [X-ray (true a.p., Bernageau and axillary views) and computed tomography (CT)] outcome parameters were assessed. RESULTS: Fourteen patients [mean age 31.1 (range 18-50) years] were available after a follow-up period of 78.7 (range 60-110) months. The SSV averaged 87 (range 65-100) %, CS 94 (range 83-100) points, RS 89 (range 30-100) points, WD 87 (range 25-100) points, and WOSI 70 (range 47-87) %. The apprehension sign was positive in two patients (14%). One patient required an arthroscopic capsular plication due to a persisting feeling of instability, while the second patient experienced recurrent dislocations after a trauma, but refused revision surgery. CT imaging showed a significant increase of the glenoid index from preoperative 0.8 ± 0.04 (range 0.7-0.8) to 1.0 ± 0.11 (range 0.8-1.2) at the final follow-up (p < 0.01). CONCLUSION: Arthroscopic reconstruction of anteroinferior glenoid defects using an autologous iliac crest bone-grafting technique yields satisfying clinical and radiologic results after a mid- to long-term follow-up period. Postoperative re-dislocation was experienced in one (7.1%) of the patients due to a trauma and an anatomic reconstruction of the pear-shaped glenoid configuration was observed. LEVEL OF EVIDENCE: IV.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".