Comparing damage on retrieved total elbow replacement bushings with lab worn specimens subjected to varied loading conditions
Bibliographic record
Abstract
ABSTRACT Complication rates following total elbow replacement (TER) with conventional implants are relatively high due to mechanical failure involving the UHMWPE bushings. Unfortunately, there are no standardized pre‐clinical durability testing protocols for assessing the durability of TER components. This study examines the damage observed on retrieved humeral bushings, and then uses in vitro durability testing with two different loading protocols to compare resulting damage. Damage on 25 pairs of retrieved humeral bushings was characterized using micro‐computed tomographic imaging techniques. The damage was compared with that of in vitro test specimens which were subjected to 200 K cycles of either high joint reaction force (high JRF) or high varus moment (high VM) loading. Material removal (mass loss) from bushing components was measured using gravimetric techniques. Thinning was less for retrieved bushings which were still assembled in their humeral component, versus bushings which were loose (0.3 ± 0.3 mm vs. 0.6 ± 0.3 mm, p = 0.02). Comparing in vitro test specimens, thinning due to high VM loading was 0.9 ± 0.3 mm, versus 0.2 ± 0.0 mm for high JRF loading (p = 0.08); however, the actual material removal rates from the humeral bushings were not different between the two protocols (48 ± 5 mm3/Mc vs. 43 ± 2 mm3/Mc, p = 1). Neither loading protocol could produce damage patterns fully representative of the spectrum of damage patterns observed on clinical retrievals. Pre‐clinical testing should employ multiple loading protocols to characterize implant performance under a broader spectrum of usage. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1998–2006, 2018.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".