Estimation of Urinary C-terminal Telopeptide of Type II Collagen and its Correlation with Radiological Grading, Pain, and Function in Patients with Primary Osteoarthritis of the Knee
Bibliographic record
Abstract
Objective: To estimate the level of urinary C-terminal telopeptide of type II collagen (uCTX-II) as a biomarker of cartilage turnover and to determine its correlation with radiological grading, pain, and functions of patients with knee osteoarthritis (OA). Methods: A descriptive cross-sectional study was conducted between September 2017 and August 2019 on 102 patients suffering from knee OA. Detailed demographic data were collected. uCTX-II level was measured for each patient. Radiological grading, pain and functional assessments were performed using Kellgren-Lawrence (K-L) grading, visual analogue scale (VAS), and Western Ontario and McMasters Universities Osteoarthritis Index (WOMAC). Results: The mean age of 62.3 (6.4) years and most patients (n = 56, 54.9%) were 61–70 years old. Females constituted 80.4% (n = 82). Among the occupations, housewives were more affected (55.9%, n = 57). Out of 102 patients, 32 (31.4%) had VAS pain 4, 25 (24.5%) had 5 and 45 (44.1%) had 6; 9 (8.8%) had K-L score 1, 51 (50%) had 2, 41 (40.2%) had 3 and 1 (1%) had 4; 35(34.3%) had WOMAC score <30, 59 (57.8%) had 30–40, and 8 (7.8%) had >40; 55 ( 53.9%) had uCTX-II level <50 ng/mmole, 25 (24.5%) had between 50 and 200 ng/mmole and 22 (21.6%) had >200 ng/mmole. There was a positive correlation between uCTX-II and WOMAC ( P = .006) and VAS ( P = .042). Conclusion: The present study findings highlighted that higher levels of uCTX-II were associated with higher levels of pain and greater difficulty with daily activities (measured by WOMAC disability score). This suggests that uCTX-II could be a useful biomarker for monitoring cartilage turnover in patients with knee OA and its relationship with pain and functional abilities.
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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) | 0.001 | 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".