The John Insall Award :Patella Resurfacing versus Nonresurfacing in Total Knee Arthroplasty
Bibliographic record
Abstract
Patellar resurfacing in total knee arthroplasty remains controversial. This study evaluates the results of resurfacing and nonresurfacing the patella in a randomized controlled, clinical trial at a minimum of 10 years followup. One hundred knees (90 patients) with osteoarthritis were enrolled in a prospective randomized clinical trial using a posterior–cruciate-retaining total knee arthroplasty. Patients were randomized to receive resurfacing or retention of the patella. Evaluations were done preoperatively and yearly, up to a minimum of 10 years (range, 10.1–11.5 years) postoperatively. Disease-specific (Knee Society clinical rating score) and functional (stair climbing, flexion/extension torques, patellar examination) outcomes were measured. Patient satisfaction, anterior knee pain, and patellofemoral questionnaires were completed. Intraoperative grading of the articular cartilage was done. No patients were lost to followup; 45 patients remained alive. Nine revisions (in nine of 90 knees; 10%) were done in seven patients in the nonresurfaced group (15% of knees) and in two patients in the resurfaced group (5% of knees). No significant difference was found between the groups regarding revision rates, Knee Society clinical rating scores, and functional, patient satisfaction, anterior knee pain, patellofemoral, and radiographic outcomes. Intraoperative cartilage quality was not a predictor of outcome. This study currently is the longest followup of a randomized controlled, clinical trial that examines patellar resurfacing in total knee arthroplasty. The results showed no significant difference between the groups for all outcome measures at a minimum of 10 years of followup.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".