The Relationship between Vitamin D Concentrations and Knee Pain in Patients of Osteoarthritis
Bibliographic record
Abstract
Objectives. In older people Osteoarthritis (OA) and vitamin D deficiency are common health conditions. It controversial Whether vitamin D concentration is associated with knee OA or not. In this study, we aimed to determine the association between serum concentrations of vitamin D and osteoarthritic knee pain. Subjects and Methods. Vitamin D concentrations were measured with the 25 hydroxy vitamin D test in patients presenting with clinical symptoms of primary knee osteoarthritis. Osteoarthritis was graded on the Kellgren-Lawrence grading scale from anteroposterior and lateral radiographs. Height, weight, and body mass index (BMI) were recorded. Patients completed a 10-cm visual analogue scale (VAS) for indicating pain and the Western Ontario and McMaster Universities Arthritis Index (WOMAC).Vitamin D concentration was defined as severely deficient (<10 ng/mL), insufficient(10 to 19 ng/mL), or normal (20 to 50 ng/mL). Results. Of 149 patients (133 women), the mean age was 62.7 years. Mean vitamin D concentration was 10.93 ng/mL, and 89% patients were vitamin D deficient. Mean WOMAC score was 56.9, and VAS pain score was 7.5. Kellgren-Lawrence grade was 3 for 11 patients, grade 2 for 60, and grade 4 for 88. Mean BMI was 33.4. Mean values of VAS, WOMAC, and BMI did not differ by vitamin D status. Conclusion. Serum vitamin D concentration is not associated with knee pain in patients with osteoarthritis.
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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 | 0.003 |
| 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) | 0.002 | 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".