A parametric analysis of fixation post shape in tibial knee prostheses
Bibliographic record
Abstract
A primary concern of total knee replacement (TKR) is aseptic loosening of the tibial component, which may be caused by shielding of mechanical stresses in the bone and may require subsequent revision surgery. A three-dimensional (3D) finite element (FE) model has been developed to study bone and interface stresses for four different tibial prosthesis designs. The model described here incorporates orthotropic and heterogeneous bone properties with physiologically representative loading conditions. Results from this model indicate that stress distribution is affected by the incorporation of anisotropy and spatial variation of bone properties. All bone properties were mapped from published data to characterize their anisotropy and heterogeneity. Physiological loading was incorporated by mapping experimentally determined contact patterns. Convergence testing was performed to ensure model accuracy. In terms of interface forces, a tapered post decreased post shear while slightly increasing post compression compared to a cylindrical post; a post of elliptical cross-section increased post shear and decreased post compression. In terms of cancellous bone stress, tapered and elliptical posts both relieved compression compared to a cylindrical post, while a tapered post also produced increased peripheral stress. The inclusion of medial and lateral pegs in addition to a central fixation post caused localized stress shielding in the periphery of the pegs. In general, all implant models caused a reduction of cancellous bone stress plus high compression beneath the central fixation posts.
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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 | 0.004 |
| 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 | 0.001 | 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".