The use of a modular system to convert an anatomical total shoulder arthroplasty to a reverse shoulder arthroplasty
Bibliographic record
Abstract
If a modular convertible total shoulder system is used as a primary implant for an anatomical total shoulder arthroplasty, failure of the prosthesis or the rotator cuff can be addressed by converting it to a reverse shoulder arthroplasty (RSA), with retention of the humeral stem and glenoid baseplate. This has the potential to reduce morbidity and improve the results. In a retrospective study of 14 patients (15 shoulders) with a mean age of 70 years (47 to 83) we reviewed the clinical and radiological outcome of converting an anatomical shoulder arthroplasty (ASA) to a RSA using a convertible prosthetic system (SMR system, Lima, San Daniele, Italy). The mean operating time was 64 minutes (45 to 75). All humeral stems and glenoid baseplates were found to be well-fixed and could be retained. There were no intra-operative or early post-operative complications and no post-operative infection. The mean follow-up was 43 months (21 to 83), by which time the mean visual analogue scale for pain had decreased from 8 pre-operatively to 1, the mean American Shoulder and Elbow Surgeons Score from 12 to 76, the mean Oxford shoulder score from 3 to 39, the mean Western Ontario Osteoarthritis of the Shoulder Score from 1618 to 418 and the mean Subjective shoulder value from 15 to 61. On radiological review, one patient had a lucency around the humeral stem, two had stress shielding. There were no fatigue fractures of the acromion but four cases of grade 1 scapular notching. The use of a convertible prosthetic system to revise a failed ASA reduces morbidity and minimises the rate of complications. The mid-term clinical and radiological results of this technique are promising.
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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 | 0.000 |
| 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) | 0.002 | 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".