Plasma and synovial osteopontin levels, are they associated with disease severity of primary knee osteoarthritis in Egyptian patients?
Bibliographic record
Abstract
Aim of the work The aim of this study was to examine osteopontin (OPN) levels in both plasma and synovial fluid of patients with primary knee osteoarthritis (OA) and to investigate their relationship with severity of the disease. Patients and methods Fifty patients with primary knee OA were compared to twenty-five apparently healthy controls. OPN levels in plasma and synovial fluid were measured using enzyme-linked immunosorbent assay. Severity of knee pain was assessed by the Western Ontario and McMaster Universities osteoarthritis index. Radiographic grading of knee OA was performed by Kellgren–Lawrence criteria. Magnetic resonance imaging (MRI) was also performed on painful knees. Results Plasma OPN was higher in patients (159.65 ± 28.56 ng/ml) than controls (90.45 ± 23.63 ng/ml). OPN in plasma and synovial fluid was correlated with severity of knee pain ( r = 0.878, r = 0.795, P < 0.001). Cartilage loss, marginal osteophytes and subchondral bone cyst were the commonest MRI findings in knee OA. MRI detected also patients with early knee OA that were not detected by plain radiography. Conclusion OPN serves as a biochemical marker of disease severity in knee OA. It also could be predictive to the progression of disease.
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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 | 0.001 |
| 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".