Associations between proinflammatory cytokines in the synovial fluid and radiographic grading and pain-related scores in 47 consecutive patients with osteoarthritis of the knee
Bibliographic record
Abstract
BACKGROUND: One of the sources of knee pain in osteoarthritis (OA) is believed to be related to local chronic inflammation of the knee joints, which involves the production of inflammatory cytokines such as tumor necrosis factor alpha (TNFα), interleukin (IL)-6, and nerve growth factor (NGF) in the synovial membrane, and these cytokines are believed to promote pathological OA. In the present study, correlations between proinflammatory cytokines in knee synovial fluid and radiographic changes and functional scores and pain scores among OA patients were examined. METHODS: Synovial fluid was harvested from the knees of 47 consecutive OA patients, and the levels of TNFα, IL-6, and NGF were measured using enzyme-linked immunosorbent assays. Osteoarthritic knees were classified using Kellgren-Lawrence (KL) grading (1-4). The Western Ontario and McMaster University Osteoarthritis Index (WOMAC) was used to assess self-reported physical function, pain, and stiffness. RESULTS: TNFα and IL-6 were detectable in knee synovial, whereas NGF was not. TNFα was not correlated with the KL grade, whereas IL-6 had a significantly negative correlation. We observed differences in the correlations between TNFα and IL-6 with WOMAC scores and their subscales (pain, stiffness, and physical function). TNFα exhibited a significant correlation with the total score and its 3 subscales, whereas IL-6 exhibited a moderately significant negative correlation only with the subscale of stiffness. CONCLUSIONS: The present study demonstrated that the concentrations of proinflammatory cytokines are correlated with KL grades and WOMAC scores in patients with knee OA. Although TNFα did not have a significant correlation with the radiographic grading, it was significantly associated with the WOMAC score. IL-6 had a significant negative correlation with the KL grading, whereas it had only a weakly significant correlation with the subscore of stiffness. The results suggest that these cytokines play a role in the pathogenesis of synovitis in osteoarthritic knees in different ways: TNFα is correlated with pain, whereas IL-6 is correlated with joint function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".