Global prevalence of vitamin D deficiency among patients with knee osteoarthritis: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Low serum 25-hydroxyvitamin D (25[OH]D) levels affect bone remodeling, contributing to the development and progression of knee osteoarthritis (OA). Aim: This meta-analysis aimed to estimate the prevalence of vitamin D deficiency in patients with knee OA. Methods: A systematic search was conducted in Europe PMC, Google Scholar, Scopus, Scilit, and Web of Science for studies published until 8 August 2024 that reported the prevalence and contributing factors of hypovitaminosis D in knee OA patients. Study quality was assessed using the Newcastle–Ottawa Scale. A random-effect meta-analysis with Freeman–Tukey double arcsine transformation estimated the pooled prevalence of vitamin D deficiency. Results: Out of 1695 records identified, 26 studies ( n = 4248 patients) met the inclusion criteria. The pooled prevalence of vitamin D deficiency was 56.72% (95% CI: 46.93–66.25). No significant difference was observed across publication periods of 2015–2019 ( p = 0.465) and 2020–2024 ( p = 0.407). Patients with an average body mass index (BMI) ≥28 kg/m² had a higher prevalence (65.62%, 95% CI: 49.23–80.32) compared to those with BMI <28 kg/m² (37.63%, 95% CI: 24.72–51.48). The prevalence was significantly higher in European countries (65.92%, 95% CI: 47.17–82.43) than in the USA ( p = 0.046). In Asia, the Middle East, and North Africa, prevalences were 60.96% (95% CI: 42.32–78.08) and 63.11% (95% CI: 43.8–80.47), respectively. Conclusion: Over half of knee OA patients had vitamin D deficiency, with higher prevalence in Europe and among individuals with obesity. Targeted screening for 25(OH)D levels in knee OA patients is recommended.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.039 |
| 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) | 0.003 | 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".