Vascular endothelial growth factor and colour Doppler ultrasonography in knee osteoarthritis: Relation to pain and physical function
Bibliographic record
Abstract
To investigate the vascular endothelial growth factor (VEGF) levels in serum and synovial fluid of patients with knee osteoarthritis (KOA) and to determine the relationship of VEGF levels with clinical manifestation, physical function, radiographic grading and ultrasonography (US) findings. 45 patients with KOA and 15 matched control subjects were enrolled. Western Ontario McMaster Osteoarthritis index (WOMAC) was scored, knee X-rays assessed using Kellgren and Lawrence (KL) scale and superficial gray scale and colour Doppler US were done. Serum and synovial VEGF levels were analyzed. The 45 patients mean age was 56.5 ± 11.2 years; 39 females and 6 males (F:M 6.5:1). 30 (66.7%) patients had bilateral symptomatic KOA. Knee effusion was mild in 4, moderate in 26 and severe in 21. The mean WOMAC score was 70.9 ± 10.7; pain (14.7 ± 3.4); stiffness (6.2 ± 1.4) and disability (49.2 ± 12.4). The serum VEGF level was 0.29 ± 1.02 pg/ml and the synovial 0.48 ± 0.1 pg/ml both significantly increased compared to the control (0.14 ± 0.7 pg/ml and 0.33 ± 0.1 respectively, p < 0.0001). Levels in grade 3 KL were significantly increased compared to those with grades 1 or 2 (p < 0.0001) and between colour Doppler US grades 1 and 2 (p < 0.0001). A strong correlation was present between serum and synovial VEGF with X-ray and colour Doppler US grading as well as the WOMAC index (p < 0.0001). Serum and synovial VEGF correlated with clinical, functional, radiographic and US severity in KOA patients. Both VEGF and musculoskeletal ultrasound may serve as promising potential tools for evaluating disease severity in KOA.
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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) | 0.001 | 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".