Independent association of joint space narrowing and osteophyte formation at the knee with health-related quality of life in Japan: A cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: To clarify the individual associations of joint space narrowing (JSN) and osteophytosis at the knee with quality of life (QOL) in Japanese men and women using a large-scale population-based cohort from the Research on Osteoarthritis Against Disability (ROAD) study. METHODS: The associations of minimum joint space width (JSW) and osteophyte area in the medial compartment of the knee with QOL parameters, such as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), were examined. Minimum JSW and osteophyte area in the medial compartment of the knee were measured using a computer-aided system for the diagnosis of knee osteoarthritis. RESULTS: Of the 3,040 participants in the ROAD study, the present study included 2,039 participants age 40 years or older who completed the questionnaires (741 men and 1,298 women with a mean ± SD age of 68.6 ± 10.9 years). Multiple regression analysis after adjustment for age and body mass index showed that minimum JSW was significantly associated with scores on the pain domains of the WOMAC in men and women, while osteophyte area was significantly associated with scores on the physical function domains of the WOMAC in men and women. CONCLUSION: The findings of this cross-sectional study using a large-scale population from the ROAD study indicate that JSN and osteophytosis are independently associated with QOL.
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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 | 0.001 |
| 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 | 0.001 |
| 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".