Knee Pain and Structural Damage as Risk Factors for Incident Widespread Pain: Data From the Multicenter Osteoarthritis Study
Bibliographic record
Abstract
Objective To examine the longitudinal relationship of knee pain, radiographic osteoarthritis (OA), symptomatic knee OA, and knee pain severity to incident widespread pain. Methods The Multicenter Osteoarthritis Study is a longitudinal cohort of persons with or at risk of knee OA. Participants were characterized as having consistent frequent knee pain, radiographic OA (Kellgren/Lawrence scale grade ≥2), symptomatic OA, and knee pain severity at the 60‐month visit (baseline). Widespread pain was categorized as pain above and below the waist, on both sides of the body and axially, using a standard homunculus, excluding knee pain. Incident widespread pain was defined as the presence of widespread pain at 84 months in those who were free of widespread pain at baseline. We assessed the relationship of baseline radiographic OA, symptomatic OA, consistent frequent knee pain, and knee pain severity, respectively, with incident widespread pain using logistic regression, adjusting for potential confounders, including models with and without pain severity. Results At baseline, 1,129 subjects were eligible for analysis (mean ± SD age 66.7 ± 7.8 years; mean ± SD body mass index 30.1 ± 5.8 kg/m2; 52% women). Radiographic OA in either knee (adjusted odds ratio [ORadj] 0.90 [95% confidence interval (95% CI) 0.63–1.30]; P = 0.587) was not associated with incident widespread pain. Baseline bilateral consistent frequent knee pain (ORadj 2.35 [95% CI 1.37–4.03]), bilateral symptomatic OA (ORadj 2.11 [95% CI 1.04–4.24]), and knee pain severity (worst knee) (ORadj 1.11 [95% CI 1.05–1.17]; P < 0.001) were significantly associated with incident widespread pain. Conclusion Consistent frequent knee pain, symptomatic OA, and knee pain severity increased the risk of developing widespread pain, independently of structural pathology. These results suggest that knee pain, and not structural pathology, contributes to the onset of widespread 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".