Patellar resurfacing in total knee replacement
Bibliographic record
Abstract
A series of 100 consecutive osteoarthritic patients was randomised to undergo total knee replacement using a Miller-Galante II prosthesis, with or without a cemented polyethylene patellar component. Knee function was evaluated using the American Knee Society score, Western Ontario and McMaster University Osteoarthritis index, specific patellofemoral-related questions and radiographic evaluation until the fourth post-operative year, then via questionnaire until ten years post-operatively. A ten-point difference in the American Knee Society score between the two groups was considered a significant change in knee performance, with alpha and beta levels of 0.05. The mean age of the patients in the resurfaced group was 71 years (53 to 88) and in the non-resurfaced group was 73 years (54 to 86). After ten years 22 patients had died, seven were suffering from dementia, three declined further participation and ten were lost to follow-up. Two patients in the non-resurfaced group subsequently had their patellae resurfaced. In the resurfaced group one patient had an arthroscopic lateral release. There was no significant difference between the two treatment groups: both had a similar deterioration of scores with time, and no further patellofemoral complications were observed in either group. We are unable to recommend routine patellar resurfacing in osteoarthritic patients undergoing total knee replacement on the basis of our findings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".