The effect of implant linking and ligament integrity on humeral loading of a convertible total elbow arthroplasty
Bibliographic record
Abstract
BACKGROUND: Both unlinked and linked total elbow arthroplasty (TEA) implants have been employed with no consensus as to the optimal design. The present study aimed to evaluate the effect of collateral ligament integrity and implant linkage on wear-inducing loads in a convertible TEA. METHODS: Eight fresh frozen upper extremities were tested in an elbow motion simulator. A convertible TEA with an instrumented humeral stem was inserted using computer navigation. Elbow kinematics and humeral loading were recorded with the TEA both linked and unlinked. The collateral ligaments were then sectioned and testing was repeated. RESULTS: In the dependent position, there was no effect of implant linkage or ligament sectioning on humeral loading. Humeral loading was significantly greater following sectioning of the collateral ligaments but not after linking the TEA with the arm in the valgus position. Humeral loading was significantly greater after linking the TEA but not after sectioning of the collateral ligaments and with the arm in the varus position. CONCLUSIONS: Collateral ligament integrity reduces wear-inducing loads for both an unlinked and linked TEA. Linkage of a convertible TEA increases humeral loading, which may have detrimental effects on implant longevity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".