The effect of vitamin D supplementation on knee osteoarthritis: A meta-analysis of randomized controlled trials
Bibliographic record
Abstract
OBJECTIVE: We conducted a meta-analysis of RCTs to evaluate the effects of vitamin D supplementation in the prevention of symptom and structural progression of knee OA. METHODS: PubMed, Embase, and Web of Science databases were searched to identify relevant studies. Outcomes included Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain, function, stiffness, tibial cartilage volume, and serum vitamin D3 levels, and adverse events. Results were expressed as weight mean difference (WMD) with 95% confidence interval (CI), and risk ratio (RR) with 95%CI. RESULTS: Four RCTs involving 1136 patients were included in this study. Pooled estimates suggested that vitamin D supplementation was associated with a significant reduction in WOMAC pain, and WOMAC function, but not in WOMAC stiffness. Vitamin D supplementation increased the serum vitamin D3 level, but had no effect on tibial cartilage volume. Subgroup analysis showed that, a daily supplement of more than 2000 IU vitamin D significantly decreased the WOMAC pain and WOMAC function. There was no significant difference in incidence of adverse events between the vitamin D and placebo groups. CONCLUSION: Vitamin D supplementation was effective in improving the WOMAC pain and function in patients with knee OA. However, it had no beneficial effect on the prevention of tibial cartilage loss. Therefore, there is currently a lack of evidence to support the use of vitamin D supplementation in preventing the progression of knee OA.
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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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.043 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".