Vitamin D Deficiency is Associated with Knee Osteoarthritis and is Implicated in the Osteoarthritis Severity
Bibliographic record
Abstract
Background: Levels of Vitamin D may impact the development and progression of knee osteoarthritis (OA), a disorder common in elderly people The aim of this study was to investigate the association between serum Vitamin D deficiency and knee OA. Methods: One hundred twenty (40 male and 80 female) consecutive patients were recruited from the rheumatology outpatient clinic for the study. X-rays in two anterior-posterior and lateral views of the knees were performed for all patients. Staging of knee OA was done according to Kellgren-Lawrence criteria and divided into two groups; group A consisting of grades 1 and 2, and group B, consisting of grades 3 and 4. One hundred (30 male and 70 female) healthy individuals without clinical and radiographic signs of the disease were defined as a control group. Hematological and biochemical investigations, including measurement of 25-hydroxyvitamin D serum level, were performed for all participants. Pain intensity using a visual analog scale (VAS) and disease severity using the Western Ontario and McMaster Universities Arthritis Index was measured for all patients. Results: The mean age of patients and controls were 60±3.5 and 54±2.6 years, respectively. Vitamin D levels of patients and controls were 13±3.3 and 32±2.5, respectively. More severe disease and diseases with prolonged duration were associated with a lower vitamin D level, and low vitamin D levels were associated with high VAS and WOMAC. Conclusion: Vitamin D deficiency was associated with the development and the severity of knee OA as well as with the disease duration.
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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 | 0.001 |
| 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) | 0.003 | 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".