Biochemical markers of bone and cartilage remodeling in prediction of longterm progression of knee osteoarthritis.
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship between biochemical markers of bone and cartilage remodeling and severity or progression (symptoms and structure) of knee osteoarthritis (OA). METHODS: Mean and minimal joint space width (JSW) of the femorotibial joint were measured from standardized radiographs taken at baseline and at the end of a 3-year longitudinal study of patients with knee OA. Pain, stiffness, and physical function subscales of the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index were assessed at the same time points. Biochemical markers [serum keratan sulfate (KS), serum hyaluronic acid (HA), urine pyridinoline (PYD) and deoxypyridinoline (DPD), serum osteocalcin (OC), cartilage oligomeric matrix protein (COMP)] were assessed at baseline and after 1 year. RESULTS: At baseline, no significant correlations were observed between values of biochemical markers and JSW or any of the WOMAC scores. Baseline markers were not correlated with 3-year percentage changes observed in mean or minimal JSW and WOMAC scores. Changes observed after 1 year in OC and HA were significantly correlated with 3-year progression in mean JSW (r = -0.24, p = 0.04 and r = 0.27, p = 0.02, respectively) and in minimal JSW (r = -0.31, p = 0.01 and r = 0.24, p = 0.04, respectively). In patients from the lowest quartile of 1-year changes in HA (< -21.22 ng/ml), mean JSW decreased after 3 years by 0.76 (1.23) mm compared to an increase of 0.11 (0.83) mm in patients in the highest quartile (> +14.34 ng/ml) (p = 0.03). CONCLUSION: The 3-year radiological progression of knee OA could be predicted by a 1-year increase in OC or a 1-year decrease in HA levels.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| 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".