Finite element analysis part 1 of 2: Influence of short stem implant polyethylene configuration on glenohumeral joint biomechanics
Bibliographic record
Abstract
Purpose: Stress shielding in short-stem arthroplasty can cause critical metaphyseal bone loss. If the size and shape of the humeral shaft are important factors, it is unknown whether the shape of the polyethylene component in reverse shoulder arthroplasty (RSA) affects bone stress around or within the stem. We explored the impact of polyethylene shape on humeral and scapular stress distribution using a finite element model. Methods: We developed a shoulder-specific finite element model. A defined set of muscle forces was applied to simulate movements. An intact rotator cuff state and a superior deficient rotator cuff state were modelled. We used the FX V135 short stem in three conditions: total shoulder arthroplasty (TSA), and RSA with symmetrical and asymmetrical polyethylene (145°/135°). We measured biomechanical markers related to bone stress for different implant sizes. Joint kinematics and the mechanical behaviour of the implant were compared. Results: Rupture of the supraspinatus muscle produced a functionally limited shoulder. The placement of an anatomic TSA with an intact rotator cuff restored function similar to that of a healthy shoulder. RSA in the rotator cuff-deficient shoulder restored function regardless of stem size and polyethylene shape. While stem size had an impact on the stress distribution in the bone and implant, it did not show significant potential for increasing or decreasing overall stress. For the same stem, stress distribution at the humerus is different between TSA and RSA. Polyethylene shape did not alter the transmission of stress to the bone in RSA. Asymmetric polyethylene produced a greater abduction range of motion. Conclusions: In terms of bone stress distribution, smaller stems seemed more appropriate for TSA, while larger stems may be more appropriate for RSA. Polyethylene shape resulted in different ranges of motion but did not influence bone stress. Level of Evidence: Diagnostic Tests or Criteria; Level IV.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".