Ten-year Results of an Inset Biconvex Patella Prosthesis in Primary Knee Arthroplasty
Bibliographic record
Abstract
UNLABELLED: The inset biconvex patella component is an alternative form of patella resurfacing in knee arthroplasty. We retrospectively reviewed 433 patients in whom 521 patella prostheses were implanted before April 1997 to determine survivorship, factors associated with failure of the implant, incidence of anterior knee pain, and factors that may be associated with the latter. We had clinical results for 204 surviving patients (242 knees) without failure of their implants with a minimum 10-year followup (mean, 11.4 years; range, 10-17 years). For the remaining 229 patients we used chart or radiographic review to determine if failure of their implant or other complications had occurred. At latest followup, 14 patella components had been revised for aseptic reasons or were radiographically loose. The 10-year Kaplan-Meier survivorship for the entire cohort for aseptic failure was 97.0%. Aseptic failure of the patella component was associated with the presence of osteonecrosis and the absence of a superior rim of bone radiographically. The incidence of anterior knee pain in surviving patients without failure of their implants was 7.8%. No factor examined was associated with anterior knee pain. Survivorship and clinical and radiographic results are equivalent, but not clearly superior, to those reported for other forms of patella resurfacing. LEVEL OF EVIDENCE: Level IV, therapeutic study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".