Biomarker of extracellular matrix remodelling C1M and proinflammatory cytokine interleukin 6 are related to synovitis and pain in end-stage knee osteoarthritis patients
Bibliographic record
Abstract
Little is known about local and systemic biomarkers in relation to synovitis and pain in end-stage osteoarthritis (OA) patients. We investigated the associations between the novel extracellular matrix biomarker, C1M, and local and systemic interleukin 6 (IL-6) with synovitis and pain. Serum C1M, plasma, and synovial fluid IL-6 (p-IL-6, sf-IL-6) were measured in 104 end-stage knee OA patients. Contrast-enhanced magnetic resonance imaging was used to semiquantitatively assess an 11-point synovitis score; pain was assessed by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Neuropathic Pain Questionnaire (NPQ). Linear regression was used to investigate associations between biomarkers and synovitis, and biomarkers and pain while controlling for age, sex, and body mass index. We also tested whether associations between biomarkers and pain were confounded by synovitis. We found sf-IL-6 was associated with synovitis in the parapatellar subregion (B = 0.006; 95% confidence interval [CI] 0.003-0.010), and no association between p-IL-6 and synovitis. We also observed an association between C1M and synovitis in the periligamentous subregion (B = 0.013; 95% CI 0.003-0.023). Furthermore, sf-IL-6, but not p-IL-6, was significantly associated with pain, WOMAC (B = 0.022; 95% CI 0.004-0.040), and NPQ (B = 0.043; 95% CI 0.005-0.082). There was no association between C1M and WOMAC pain, but we did find an association between C1M and NPQ (B = 0.229; 95% CI 0.036-0.422). Lastly, synovitis explained both biomarker-NPQ associations, but not the biomarker-WOMAC association. These results suggest that C1M and IL-6 are associated with synovitis and pain, and synovitis is an important confounding variable when studying biomarkers and neuropathic features in OA patients.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".