Interleukin-34 Synovial Fluid Was Associated with Knee Osteoarthritis Severity: A Cross-Sectional Study in Knee Osteoarthritis Patients in Different Radiographic Stages
Bibliographic record
Abstract
Background . Inflammation might play a crucial role in the pathogenesis of osteoarthritis (OA). Interleukin-34 (IL-34) is a well-known proinflammatory cytokine. Objective . The objective of this study was to detect IL-34 levels in serum and synovial fluid (SF) of patients with OA and to investigate their correlation with radiographic and symptomatic severity. Methods . One hundred and eighty-two OA patients and 69 controls were recruited. IL-34 levels were measured by enzyme-linked immunosorbent assay (ELISA). Radiographic and symptomatic severity of OA was reflected by Kellgren-Lawrence (KL) grades and Western Ontario McMaster University Osteoarthritis Index (WOMAC) scores, respectively. Results . SF IL-34 levels were independently associated with the KL grade ( B = 0.273 , 95% CI: 0.150–0.395; P < 0.001 ). SF IL-34 levels were significantly correlated with WOMAC scores ( r = 0.265 , 95% CI: 0.123–0.399; P < 0.001 ). The correlation between SF IL-34 levels and WOMAC scores was still significant after adjusting for confounding factors ( B = 0.020 , 95% CI: 0.001–0.038; P = 0.035 ) in OA patients. Conclusions . We found that IL-34 levels in SF were significantly associated with the radiographic and symptomatic severity of knee OA.
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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 | 0.001 | 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) | 0.002 | 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".