The association of plasma IL-1Ra and related cytokines with radiographic severity of early knee osteoarthritis
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Bibliographic record
Abstract
We aimed to evaluate the association between inflammatory biomarkers in peripheral blood and severity of knee osteoarthritis (OA). We performed a cross-sectional study in participants with frequent knee pain, evaluated radiographic and clinical severity. We measured inflammatory biomarkers: plasma (p) IL-1Ra, IL-1β, IL-18, serum (s) CD14, hsCRP and bone and cartilage biomarkers: urine (u) CTX-II, (s) HA, COMP, CTX-I, PIIANP. We assessed radiographic severity by Kellgren-Lawrence (KL) grading and Osteoarthritis Research Society International (OARSI) standardized scoring atlas; and clinical severity by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). 139 participants (82% women, mean ± SD age: 55.5 ± 7.8 years) were included. (p) IL-1Ra was negatively associated with radiographic severity by KL grading (Spearman rho = −0.197, P = 0.021), osteophytes (Spearman rho = −0.217, P = 0.011), and joint space narrowing of index knee (Spearman rho = −0.172, P = 0.045); and KL sum score of both knees (Spearman rho = −0.180, P = 0.035), after adjustment for age, gender and body mass index (BMI). Other inflammatory markers were not associated with radiographic severity. Cartilage degradation markers (u) CTXII and (s) COMP were modestly associated with radiographic severity after adjustment. In multivariate models, (s) hsCRP and the bone and cartilage biomarkers, but not the inflammatory biomarkers, were associated with radiographic severity. Among the inflammatory biomarkers in peripheral blood, IL-1Ra was negatively associated with radiographic severity in this early knee OA cohort.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it