Arthroscopic reduction and subscapularis remplissage (ARR) of chronic posterior locked shoulder dislocation leads to optimized outcomes and low rate of complications
Bibliographic record
Abstract
PURPOSE: Unrecognized posterior shoulder dislocation with a concomitant humeral head fracture affects joint function and no consensus exists regarding treatment. The present study analyses clinical and radiographic outcomes of a novel arthroscopic technique for reducing chronic locked posterior shoulder dislocation associated with subscapularis remplissage. METHODS: The study comprises a retrospective analysis of consecutive chronic posterior locked shoulders (CPLS) with minimum 2-years follow-up of patients who had undergone McLaughlin technique arthroscopic modification for the treatment of CPLS with a reverse Hill-Sachs lesion. Active range of motion (ROM), Western Ontario (WOSI) and Constant Score (CS), were evaluated pre- and postoperatively. Plain radiographs and magnetic resonance imaging (MRI) scans were collected pre- and post-operatively, recording bone defect, osteoarthritis, cuff integrity/fatty infiltration, and the grade of filling of the reverse Hill-Sachs. RESULTS: Twelve male patients with a mean follow-up of 37.3 months ± 10.5 (range, 24-58) were included. Mean WOSI and CS scores improved from 41 to 92 and 28 to 94 points, respectively. ROM measurements all had significantly increased at final follow-up, with no significant differences in arm rotation. No defects were left unfilled at final MRI examination. CONCLUSION: The results of this uncontrolled study with a limited number of patients confirm that arthroscopic reduction and subscapularis remplissage is a highly effective and satisfactory treatment method resulting in no shoulder rotation deficits. LEVEL OF EVIDENCE: Level 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".