Correlation between synovial vascular endothelial growth factor, clinical, functional and radiological manifestations in knee osteoarthritis
Bibliographic record
Abstract
To correlate between synovial vascular endothelial growth factor (VEGF), clinical, functional and radiological findings in knee osteoarthritis (KOA) patients. Twenty patients with primary KOA were clinically examined and the modified Ritchie articular index (RAI) recorded. The knees were examined and knee pain evaluated by the visual analog scale (VAS) and tenderness by the knee subscale of the RAI. The Western Ontario Mc Master scale (WOMAC) was recorded and the Kellgren–Lawrence grading used to assess radiographic severity. The synovial level of VEGF was assessed using ELISA. The mean age was 56.15 ± 7.77 years and body mass index 28.1 ± 4.04. All patients had knee effusion; 40% were bilateral and 60% unilateral. The mean duration of knee pain was 3.01 ± 1.43 years; duration of morning stiffness was 15.75 ± 3.72 min. The mean WOMAC was 44.22 ± 11.46 and modified RAI 5.45 ± 2.94. The mean knee subscale of RAI was 2.9 ± 1.16 and VAS for knee pain 5.7 ± 2.92. The mean synovial VEGF level was 693.71 ± 314.63 pg/ml. There was a significant increase in the synovial VEGF compared to the reference value (p = 0.0001). There was a significant correlation between the synovial VEGF and patients’ age (p = 0.04), knee pain duration (p = 0.025), morning stiffness (p < 0.0001), modified RAI (p = 0.0001), knee subscale of RAI (p < 0.0001), VAS for knee pain (p < 0.0001) and WOMAC (p = 0.0001). There was a significant negative correlation between synovial VEGF and muscle strength grading (p = 0.0001) and a significant correlation with the radiological assessment (p = 0.0001). Synovial VEGF significantly correlated with clinical manifestations, functional impact, as well as radiological changes of 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 | 0.001 |
| 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) | 0.002 | 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".