Two cases of sternoclavicular joint replacement arthroplasty: A case report. A novel prosthesis and surgical technique for recalcitrant instability, arthropathy of the sternoclavicular joint with medial clavicular bone loss
Bibliographic record
Abstract
Instability arthropathy of the sternoclavicular joint is most commonly managed by rehabilitation, injection, and either arthroscopic or open debridement with or without interposition arthroplasty. When these options fail to achieve symptom relief, excision arthroplasty is an option. This is associated with a risk of persistent instability and incomplete pain relief. We describe two cases in which custom sternoclavicular joint replacement was performed for painful insufficiency of scapular suspension. Although the prostheses remained secure in both cases, the first case was complicated by persistent instability due to insufficient reconstruction of the intrinsic sternoclavicular capsular ligaments. This was recognised and corrected for in the second case, in which stability of the sternoclavicular joint replacement has been noted on more than a 5-year review. We conclude that sternoclavicular joint replacement is an option for patients in whom instability arthropathy remains an intrusive problem in daily life after other conventional treatments have not controlled symptoms. Stability of the joint remains a concern. We offer one method of achieving stability through an iterative design process including the ability to reconstruct the intrinsic capsular ligaments around the articulation.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".