Anatomical total shoulder replacement with rotator cuff repair for osteoarthritis of the shoulder
Bibliographic record
Abstract
We assessed the clinical results, radiographic outcomes and complications of patients undergoing total shoulder replacement (TSR) for osteoarthritis with concurrent repair of a full-thickness rotator cuff tear. Between 1996 and 2010, 45 of 932 patients (4.8%) undergoing TSR for osteoarthritis underwent rotator cuff repair. The final study group comprised 33 patients with a mean follow-up of 4.7 years (3 months to 13 years). Tears were classified into small (10), medium (14), large (9) or massive (0). On a scale of 1 to 5, pain decreased from a mean of 4.7 to 1.7 (p = < 0.0001), the mean forward elevation improved from 99° to 139° (p = < 0.0001), and the mean external rotation improved from 20° (0° to 75°) to 49° (20° to 80°) (p = < 0.0001). The improvement in elevation was greater in those with a small tear (p = 0.03). Radiographic evidence of instability developed in six patients with medium or large tears, indicating lack of rotator cuff healing. In all, six glenoid components, including one with instability, were radiologically at risk of loosening. Complications were noted in five patients, all with medium or large tears; four of these had symptomatic instability and one sustained a late peri-prosthetic fracture. Four patients (12%) required further surgery, three with instability and one with a peri-prosthetic humeral fracture. Consideration should be given to performing rotator cuff repair for stable shoulders during anatomical TSR, but reverse replacement should be considered for older, less active patients with larger tears.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".