The effect of component offset on acromion and scapular spine strains following reverse total shoulder arthroplasty: An ex-vivo shoulder motion study
Bibliographic record
Abstract
The effects of component offset in reverse total shoulder arthroplasty (rTSA) on acromion and scapular spine strains are not well understood, and no comparison of strain patterns between the native and implanted shoulder exists. This study investigated the effects of humerus distalization, humerus lateralization, glenosphere lateralization, and humerus-to-glenosphere lateralization ratio in rTSA on acromion and scapular spine strains during simulated unconstrained shoulder motion and compared the observed strain patterns to the native condition. Seven cadaveric specimens were tested on a shoulder simulator which performed scapular plane abduction and internal-external rotation. Maximum principal strain was measured in four clinically relevant regions according to the Levy classification system using strain gauge rosettes. Overall, rTSA conditions had higher strains than the native condition at low elevation (p < 0.05) but not at high elevation. During scapular plane abduction, strain peaked at low elevation for all reverse conditions, but at high elevation angles in the native condition. Strain increased significantly with humerus distalization in Levy 3A (p = 0.038), while strain decreased significantly in all regions with humerus lateralization (p ≤ 0.049). Isolated glenosphere lateralization had no effect on scapula strains (p ≥ 0.162) while humerus-sided lateralization resulted in significantly less strain than combined humerus and glenosphere lateralization (p ≤ 0.015). RTSA alters the strain patterns on the acromion and scapular spine from those observed in the native shoulder. In addition, component offset had significant effects on scapula strains demonstrating that implant configuration likely has an influence on the occurrence of acromion and scapular spine fractures.
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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".