Effect of vitamin D deficiency on osteoarthritis and bone mineral density in elderly patients
Bibliographic record
Abstract
Purpose: We aimed to determine the effect of inadequate vitamin D level on osteoartritis (OA) and bone mineral density (BMD) in female and male elderly patients with early and late stage OA with different BMD, and also the relationship between vitamin D and knee function scores in female and male OA patients.Materials and Methods: One hundred and fortytwo female and one hundred thirty-five male knee OA patients were enrolled in the study. The knee OA was classified as early and late stage. WOMAC score, KOOS score, BMD and Vitamin D levels were measured. Results: Vitamin D levels patients were statistically significantly lower in female OA than male OA group. Calcium and phosphorus levels were significantly higher in female OA patients than male OA group. There was no difference between vitamin D, vitamin B12, calcium, phosphorus, WOMAC score and KOOS scores in early and late stage OA patients with osteoporosis, osteopenia and normal BMD. WOMAC score was significantly higher in male patients with osteoporosis early stage and late stage OA than patients with osteopenia and normal BMD. The age odds ratio (OR) was 1,047 (95% CI = 1,009-1,086) in female OA patients, and OR was 1.090 (95% CI = 1,021-1,163) in male OA patients.Conclusion: Vitamin D supplementation may be said increase BMD, slow down the progression of osteoporosis, reduce pain, but have no effect on OA progression and knee function scores.
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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 | 0.001 |
| 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) | 0.001 | 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".