Does Bearing Design Influence Midterm Survivorship of Unicompartmental Arthroplasty?
Bibliographic record
Abstract
UNLABELLED: Medial unicompartmental arthroplasties (UKA) are available with mobile- and fixed-bearing designs, with the advantages of one bearing over another unproven. We questioned whether the bearing design influenced clinical outcome, survivorship, the reason for revision, or the timing of failures. We retrospectively reviewed 179 patients (229 knees) who had medial unicompartmental knee arthroplasties between 1990 and 2007; of these 79 knees had a mobile-bearing design and 150 knees a fixed-bearing design. Patients with mobile-bearing UKA had a minimum followup of 1 year (mean, 3.6 years; range, 1-11.3 years); those with fixed-bearing UKA a minimum followup of 1 year (mean, 8.1 years; range, 1-17.8 years). Patients were evaluated with clinical outcome scores and radiographically using the Knee Society rating system. Seven of 79 (9%) mobile-bearing knees underwent revision at a mean of 2.6 years, and 22 of 150 (15%) fixed-bearing knees underwent revision at a mean of 6.9 years. The 5-year cumulative survival rates were 88% (SE +/- 0.47, 95% CI 0.7229-1) and 96% (SE +/- 0.16, 95% CI 0.93-0.9979) for the mobile- and fixed-bearing designs respectively using the endpoint of revision surgery. We observed no differences in the indications or complexity of revision surgery between the groups and none in midterm survivorship. LEVEL OF EVIDENCE: Level III, comparative study. See Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".