The effect of humeral polyethylene insert constraint on reverse shoulder arthroplasty biomechanics
Bibliographic record
Abstract
Background There is little information on the effects of altering reverse shoulder arthroplasty (RSA) polyethylene constraint on joint load, load angle and deltoid force. The present biomechanical study aimed to investigate the effects of changing RSA polyethylene constraint on joint load, load angle, deltoid force and range of motion. Methods A custom RSA implant capable of measuring forces across the joint with varying polyethylene constraint was tested in six cadaveric shoulders. Standard-, low- and high-constraint (retentive) polyethylene liners were tested, and joint kinematics, loads and muscle forces were recorded. Results When polyethylene constraint was altered, joint load and load angle during active abduction were not affected significantly ( p > 0.19). Additionally, the force required by the deltoid for active abduction was not affected significantly by cup constraint ( p = 0.144). Interestingly, active abduction range of motion was also not affected significantly by changes in cup constraint ( p > 0.45). Conclusions Altering polyethylene cup constraint in RSA to enhance stability does not significantly alter resultant joint loads and deltoid forces. Surprisingly, terminal abduction range of motion was also not significantly different with varying cup constraint, indicating that terminal impingement may be tuberosity related rather than polyethylene.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".