Difference in Postoperative Outcomes and Satisfaction Between Men and Women After Total Knee Arthroplasty
Bibliographic record
Abstract
Background This study was conducted to determine the difference in clinical outcomes and satisfaction between men and women after total knee arthroplasty (TKA) and whether the relationship between postoperative outcomes and satisfaction differs between the 2 groups after TKA. Materials and Methods This retrospective study included 324 patients who underwent TKA. The participants were divided by sex as follows: male (n=130) and female (n=194). The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, Knee Society Score (KSS), and satisfaction score and their correlation coefficients at 1 and 2 years after TKA were compared between the groups. Results The satisfaction scores of the male and female patients were 27.1 and 22.7, respectively ( P <.001), 1 year after TKA and 29.7 and 29.2, respectively ( P =.575), 2 years after TKA. No significant differences in the WOMAC score or KSS were observed between the 2 groups. The correlation coefficients between the satisfaction score and WOMAC score or KSS (function scores) were higher for women than for men 1 and 2 years after TKA (1-year WOMAC score: men, −0.682; women, −0.724; 1-year KSS function score: men, 0.500; women, 0.795) (2-year WOMAC score: men, −0.536; women, −0.778; 2-year KSS function score: men, 0.444; women, 0.702). Conclusion The early postoperative satisfaction of female patients was lower than that of male patients but eventually improved to the satisfaction level of male patients, and the association between outcomes and satisfaction within 2 years after TKA was higher for female patients than for male patients. [ Orthopedics . 2025;48(2):121–127.]
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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 | 0.003 |
| 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 | 0.000 |
| 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 | 0.000 |
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".