Reverse shoulder arthroplasty glenoid lateralization influences scapular spine strains
Bibliographic record
Abstract
BACKGROUND: Scapular spine insufficiency fractures following reverse shoulder arthroplasty are poorly understood. There exists limited literature regarding the role of reverse shoulder arthroplasty lateralization on scapular spine strains and fractures. The purpose of this cadaveric biomechanical simulator study was to evaluate the role of glenoid lateralization on scapular spine strain. METHODS: Eight cadaveric shoulders were tested using an in-vitro simulator. A custom modular reverse shoulder arthroplasty was implanted that allowed for in-situ glenoid lateralization adjustment. Scapular spine strain was measured by strain gauges placed in clinically relevant Levy zones along the scapular spine. All specimens were tested in loaded forward elevation and abduction. RESULTS: Glenoid lateralization from 0 to 5 mm caused negligible changes in scapular spine strains. Lateralization from 5 to 10 mm, however, caused significant increases in strain at 0° forward elevation in all strain gauges (p < 0.026). Strains measured in Levy zone 2 were significantly higher than all other locations (p < 0.039). Additionally, forward elevation resulted in significantly higher strain values than abduction (p = 0.001). CONCLUSIONS: Glenoid lateralization is an important parameter in reverse shoulder arthroplasty; however, our results demonstrate higher degrees of lateralization may place higher strains on the scapular spine. An understanding of reverse shoulder arthroplasty lateralization and scapular spine strains is important to optimize parameters and to mitigate negative effects. LEVEL OF EVIDENCE: Basic Sciences Study, Cadaveric Model, Biomechanics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".