The relationship between synovial fluid <scp>VEGF</scp> and serum leptin with ultrasonographic findings in knee osteoarthritis
Bibliographic record
Abstract
AIM: This study aimed to determine synovial fluid and serum biomarkers which could accord with radiological and ultrasonographic findings in knee osteoarthritis. METHODS: Thirty-four patients with knee osteoarthritis were detected with joint effusion by clinical examination. Both knee joints were examined using plain radiographs and ultrasonography. Questions were obtained for visual analog scale (VAS), Western Ontario McMaster Universities Osteoarthritis Index and Health Assessment Questionnaire (HAQ). Synovial fluid (SF) and serum levels of vascular endothelial growth factor (VEGF), matrix metalloproteinase (MMP)-13, leptin, resistin and cartilage oligomeric matrix protein (COMP) were measured using enzyme-linked immunosorbent assay. RESULTS: Synovial fluid VEGF level was positively correlated with Kellgren-Lawrence (KL) grades and it was higher in patients with KL grade 4 than those with KL grade 2. SF VEGF correlated with ultrasonographic findings, such as the length of medial osteophytes. The amount of effusion was positively correlated with SF resistin. Serum leptin level had positive correlation with HAQ and the length of medial osteophytes. MMP-13 or COMP levels were not correlated with radiographic or ultrasonographic findings. CONCLUSION: Synovial fluid VEGF level was correlated with radiographic grading, ultrasonographic findings and functional statues in knee osteoarthritis, and serum leptin level also correlated with the ultrasonographic findings and functional status of knee osteoarthritis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".