Fibulin-3 serum and urine levels in the diagnosis and severity assessment of primary knee osteoarthritis
Bibliographic record
Abstract
Objectives Osteoarthritis (OA) is the most widespread joint disease and is a major cause of joint pain and disability in the middle aged and elderly population. The diagnosis of OA is based on clinical and radiographic changes that occur late after disease progression, and hence does not allow early detection of structural damage. Therefore, there is an acute need for reliable biochemical markers that can facilitate its earlier diagnosis. This study was commenced to identify fibulin-3 levels in serum and urine of patients with primary knee OA and to investigate their relationship with severity of the disease. Material and methods Fifty female patients with primary knee OA were compared to 25 healthy female controls. Fibulin-3 in serum and urine were measured using enzyme-linked immunosorbent assay (ELISA). Severity of knee pain was assessed by the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index and the Knee Outcome Survey Activities of Daily Living (KOS-ADL) scale. Radiographic grading of knee OA was performed by Kellgren-Lawrence (K-L) criteria. Results Serum and urine fibulin-3 were higher in patients (286.00 ±145.00 ng/ml and 104.60 ±32.73 ng/ml, respectively) than in controls (26.00 ±5.77 ng/ml and 13.60 ±4.21 ng/ml, respectively). Fibulin-3 in serum and urine correlated (p < 0.001) with each other (r = 0.930) and with the severity of knee pain by WOMAC index (r = 0.909 and 0.928, respectively), inversely correlated with KOS-ADL (r = –0.913 and –0.953, respectively), and with radiographic grading of K-L (r = 0.855 and 0.875, respectively). Conclusions Fibulin-3 serves as a biomarker of knee OA disease severity and could predict disease progression. Assessing urine fibulin-3 could be an applicable and easy method to diagnose knee OA and to follow up disease progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".