Comparison of standard and gender-specific posterior-cruciate-retaining high-flexion total knee replacements
Bibliographic record
Abstract
We undertook a study in which 138 female patients with a mean age of 71.2 years (51 to 82) received a standard NexGen CR-flex prosthesis in one knee and a gender-specific NexGen CR-flex prosthesis in the other. The mean follow-up period was 3.25 years (3.1 to 3.5). The aspect ratios of the standard and gender-specific prostheses were compared with that of the distal femur. The mean post-operative Knee Society knee scores were 94 (70 to 100) and 93 (70 to 100) points and the function scores were 83 (60 to 100) and 84 (60 to 100) points for the standard implants and the gender-specific designs, respectively. The mean post-operative Western Ontario and McMaster Universities score was 26.4 points (0 to 76). Patient satisfaction, the radiological results and the complication rates were similar in the two groups. In those with a standard prosthesis, the femoral component was closely matched in 80 knees (58.0%), overhung in 14 (10.1%) and undercovered the bone in 44 (31.9%). In those with a gender-specific prosthesis, it was closely matched in 15 knees (10.9%) and undercovered the bone in 123 (89.1%). Since we found no significant differences between the two groups with regard to the clinical and radiological results, patient satisfaction or complication rate, the goal of the design of the gender-specific CR-flex prosthesis to improve the outcome was not achieved in our patients.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".