The 2012 Mark Coventry Award: A Retrieval Analysis of High Flexion versus Posterior-stabilized Tibial Inserts
Bibliographic record
Abstract
BACKGROUND: High flexion (HF) implants were introduced to increase ROM and patient satisfaction, but design changes to the implant potentially have deleterious effects on polyethylene wear. It is unclear whether the HF implants affect wear. QUESTIONS/PURPOSES: We therefore examined whether the design changes between HF and posterior-stabilized (PS) tibial inserts would affect overall damage or damage on their articular surface, backside, and tibial post and whether flexion angle achieved related to damage. METHODS: We matched 20 retrieved HF inserts to 20 retrieved PS inserts from the same implant system on the basis of duration of implantation, body mass index, and age. Inserts were divided into 16 zones and a microscopic analysis of surface damage was carried out. Five inserts were scanned using micro-CT to further quantify instances of severe post notching. We determined overall damage with a scoring system. RESULTS: We found greater backside and post damage in the HF group but no difference in the articular surface or overall damage scores. Backside and post damage scores correlated to flexion angle in the HF group. There was no flexion/damage correlation in the PS group. Notch depths around the post in both groups ranged from 0.6 to 1.9 mm. CONCLUSIONS: HF inserts are more susceptible to post damage, possibly as a result of higher contact stresses from greater flexion. The increased backside damage was unexpected because the two groups have the same tibial component, locking mechanism, and sterilization method. CLINICAL RELEVANCE: The introduction of a highly crosslinked HF insert will require close scrutiny as a result of the potential for post damage demonstrated in this series.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".