Effects of Prosthetic Mismatch and Subscapularis Tear on Glenohumeral Contact Patterns in Total Shoulder Arthroplasty: A Numerical Musculoskeletal Analysis
Bibliographic record
Abstract
Prosthetic components' mismatch and subscapularis (SC) tear are determining factors for glenoid failure complication in nonconforming total shoulder arthroplasty (NC-TSA). Risk factors are linked to glenoid prosthetic loading. However, the mechanisms underlying the clinical observations remain unclear. This study assessed the combined impact of mismatch and subscapularis tear on glenoid loading. It was assumed that adequate glenoid loading was associated with minimal, but non-null, humeral head translations and contact pressure, as well as with maximal glenoid contact area, and that the center of pressure (COP) on the glenoid would have a centered displacement pattern. A numerical model was used to achieve two objectives. The first was to verify whether an optimum mismatch existed, for which failure risk would be minimal. The second was to explore the effect of subscapularis tear on the position of applied forces on the glenoid. A shoulder AnyBody musculoskeletal model was adapted to the arthroplasty context by introducing humeral head translations and contact between implants. Ten simulations were computed to compare combinations of varying mismatches (1.4 mm, 3.4 mm, 6.4 mm, 8.6 mm, and 9 mm) with two shoulder conditions (intact-muscle or subscapularis tear). Humeral head translations, center-of-pressure, contact area, contact pressure, and glenohumeral joint contact forces were numerically estimated. Mismatches between 3.4 mm and 6.4 mm were associated with the most minimal humeral translations and contact pressure, as well as with maximal contact area. Center of pressure displacement pattern differed according to shoulder condition, with an outward anterior tendency in presence of tear.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".