Correlation Between Vitamin D and Degenerative Joint Disorders: Review and Meta-Analysis
Bibliographic record
Abstract
Objective: Evaluate the evidence of the clinical correlation between vitamin D and symptomatic degenerative joint disease. Methods: A systematic search and meta-analysis was conducted of randomized controlled studies (RCTs) published in between January 1st, 2010, and March 30th, 2020 on five different databases. The study population consisted of adult patients with symptomatic knee osteoarthritis; the intervention was vitamin D; the comparison was placebo, and the outcomes included the Western Ontario and McMaster Universities Arthritis Index (WOMAC) (pain, function, stiffness), tibial cartilage volume, synovial tissue volume (STV), subchondral bone marrow lesion (BML) volume, effusion-synovitis, serum vitamin D3 levels, serological inflammatory and metabolic biomarkers levels and adverse events. Results: Nine RCTs involving 2,168 patients were included in this study. Pooled estimates suggested that vitamin D supplementation was associated with reduction in WOMAC pain (Std. Mean=1.08(0.90, 1.25); I2=99%; p=0.00001), function (Mean=1.1(0.92, 1.27); I2=99%; p=0.00001), stiffness (Std. mean= 0.72(0.54, 0.90); I2=98%; p=0.00001) and synovial effusion in the suprapatellar pouch numbers. There was no significant difference in tibial cartilage volume incidence (Std. Mean=0.26(0.44, 0.80); I2=99%; p=0.00001), STV, BML volume, inflammatory biomarkers and adverse events between the vitamin D and the placebo groups. Conclusion: Vitamin D supplementation was effective in improving WOMAC pain and function in patients with knee OA and also improved serological vitamin D levels. However, it had no beneficial effect on structural cartilage change or inflammatory biomarker reduction. Therefore, there is currently a lack of evidence on vitamin D regimen dosage and length to obtain benefits in preventing knee disease progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".