Total Serum Testosterone and Western Ontario and McMaster Universities Osteoarthritis Index Pain and Function Among Older Men and Women With Severe Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate whether serum total testosterone level is associated with knee pain and function in men and women with severe knee osteoarthritis (OA). METHODS: We enrolled 272 adults age ≥60 years (mean ± SD age 70.4 ± 4.4 years, 53% women) who underwent unilateral total knee replacement (TKR) due to severe knee OA. Serum testosterone levels and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function of the operated and contralateral knee were measured at 6-8 weeks after surgery. At the nonoperated knee, 56% of participants had radiographic knee OA with a Kellgren/Lawrence grade ≥2. Cross-sectional analyses were performed by sex and body mass index (BMI) subgroups, using multivariable regression adjusted for age, physical activity, and BMI. RESULTS: At the operated knee, higher testosterone levels were associated with less WOMAC pain in men (B = -0.62, P = 0.046) and women (B = -3.79, P = 0.02), and less WOMAC disability scores in women (B = -3.62, P = 0.02) and obese men (B = -1.99, P = 0.02). At the nonoperated knee, testosterone levels were not associated with WOMAC pain in men or women, but higher testosterone levels were associated with less disability in women (B = -0.95, P = 0.02). Testosterone levels were inconsistently associated with pain and disability in BMI subgroups among men. Only among obese women, testosterone levels were inversely associated with radiographic knee OA (odds ratio = 0.10, P = 0.003). CONCLUSION: Higher total testosterone levels were associated with less pain in the operated knee in men and women undergoing TKR and less disability in women. At the nonoperated knee, higher testosterone levels were inconsistently associated with less pain and disability.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".