Association of Serum Vitamin D with Serum Cytokine Profile in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
Objective The role of vitamin D in the pathogenesis of osteoarthritis (OA) is not well understood. In this study, we aimed to investigate the association of serum vitamin D with the serum cytokine profile in patients with primary knee OA. Design In a cross-sectional study, 116 patients with radiologic diagnosis of grade I to III knee OA were included. The study population included 79 (75.9%) females and 25 (24.1%) males with a mean age of 55.1 ± 9.6 years. The serum concentration of IL-6, IL-8, TNF-α, IL-4, IL-10, IL-13, and vitamin D were assessed using an enzyme-linked immunosorbent assay. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was used for the assessment of patient’s reported disability associated with knee OA. Results Serum vitamin D status was deficient, insufficient, and sufficient in 18 (15.5%), 63 (54.3%), 35 (30.2%) patients, respectively. Higher levels of serum IL-6 were observed in patients with vitamin D deficiency ( P = 0.022). The mean serum vitamin D level was not associated with OA grade ( P = 0.88) and WOMAC scores of the patients ( P = 0.67). Serum IL-6 level was significantly associated with both OA grade and WOMAC scores of the patients ( P < 0.001 and P = 0.001, respectively). The vitamin D status was not significantly associated with the serum levels of other evaluated cytokines. Conclusion Vitamin D deficiency in knee OA seems to be associated with a higher release of IL-6. Therefore, vitamin D supplementation could reduce the disease burden by controlling the IL-6 release.
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) | 0.000 | 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".