Bone stresses before and after insertion of two commercially available distal ulnar implants using finite element analysis
Bibliographic record
Abstract
Distal ulnar arthroplasty is becoming a popular treatment option for disorders of the distal radioulnar joint; however, few studies have investigated how load transfer in the ulna is altered after insertion of an implant. The purpose of our study was to compare bone stresses before and after insertion of two commercially available cemented distal ulnar implants: an implant with a titanium stem and an implant with a cobalt chrome stem. Appropriately sized implants of both types were inserted into eight previously validated subject-specific finite element models, which were created by using information derived from computed tomography scans. The von Mises stresses were compared at eight different regions pre- and post-implantation. The bone stresses with the titanium stem were consistently closer to the pre-implantation stresses than with the cobalt chrome stem. For the loading situation and parameters investigated, results of these models show that insertion of the E-Centrix® ulnar Head may result in less stress shielding than the SBI uHead™ stem. Future studies are required to investigate other implant design parameters and loading conditions that may affect the predicted amount of stress shielding.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".