Longitudinal Relationship Between Tibiofemoral Contact Stress at Baseline and Worsening of Knee Pain Over 84 Months in the Multicenter Osteoarthritis Study
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to determine whether tibiofemoral contact stress predicts risk for worsening knee pain over 84 ms in adults aged 50-79 yrs with or at elevated risk for knee osteoarthritis. DESIGN: Baseline tibiofemoral contact stress was estimated using discrete element analysis. Other baseline measures included weight, height, hip-knee-ankle alignment, Kellgren-Lawrence grade, and Western Ontario and McMaster Universities Osteoarthritis Index pain subscale. Logistic regression models assessed the association between baseline contact stress and 84-mo worsening of Western Ontario and McMaster Universities Osteoarthritis Index pain subscale. RESULTS: Data from the dominant knee (72.6% Kellgren-Lawrence grade 0/1 and 27.4% Kellgren-Lawrence grade ≥ 2) of 208 participants (64.4% female, mean ± SD body mass index = 29.6 ± 5.1 kg/m 2 ) were analyzed. Baseline mean and peak contact stress were 3.3 ± 0.9 and 9.4 ± 4.3 MPa, respectively. Forty-seven knees met the criterion for worsening pain. The highest tertiles in comparison with the lowest tertiles of mean (odds ratio [95% confidence interval] = 2.47 [1.03-5.95], P = 0.04) and peak (2.49 [1.03-5.98], P = 0.04) contact stress were associated with worsening pain at 84 mos, after adjustment for age, sex, race, clinic site, and baseline pain. Post hoc sensitivity analyses including adjustment for body mass index and hip-knee-ankle alignment attenuated the effect. CONCLUSIONS: These findings suggest that elevated tibiofemoral contact stress can predict the development of worsening of knee pain.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".