Quality of Life of Men and Women with Osteoarthritis of the Hip and Arthroplasty
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate the differences in quality of life between men and women in preoperative and postoperative period after hip arthroplasty because of severe hip osteoarthritis. DESIGN: This is a prospective study of 160 patients (average age, 61.7 yrs), 92 women and 68 men, with a diagnosis of osteoarthritis of the hip who underwent total hip arthroplasty. All patients completed the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaires that measured health-related quality of life preoperatively, at discharge, and 6-wk postoperatively. To establish the occurrence of differences between men and women in preoperative and postoperative period after arthroplasty, Student's t test and multivariate logistic regression analysis were used. RESULTS: The WOMAC global score was a significant predictor (the better the rather men) preoperatively (P < 0.01) and 6 wks after total hip arthroplasty (P < 0.001). Global WOMAC score was significantly better in men than in women preoperatively (t = 4.02; P < 0.001) and 6 wks after arthroplasty (t = 3.42; P < 0.001). CONCLUSIONS: These results suggest that men with severe osteoarthritis of the hip have better quality of life than do women preoperatively and 6 wks after hip arthroplasty. These findings would be important for improving quality of care of 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".