Assessing the relationship between vitamin D, magnesium, and functional outcomes in knee osteoarthritis
Bibliographic record
Abstract
Introduction. Knee osteoarthritis (KOA) is the most common degenerative joint disease and a major contributor to disability, highlighting the need to assess functional status alongside clinical findings. Despite the growing incidence of KOA, no simple therapy has significantly improved its functional impairments. Identifying modifiable risk factors, such as micronutrient levels, is necessary. While current research explores the relationship between vitamin D and magnesium with KOA severity, their association with specific functional status remains unclear. This study investigates the relationship between serum vitamin D and magnesium levels with functional status in KOA patients, using total and subscale Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores. Methods. Data from clinical assessments and laboratory tests were analyzed against total WOMAC scores using Fisher's exact test, independent t-test, and Mann-Whitney test. Subscale correlations were evaluated with Pearson and Spearman tests. Results. The mean vitamin D level was 20.59 ± 5.43 ng/ml, while the median magnesium level was 1.90 mmol/L. Vitamin D showed a significant negative correlation with total WOMAC scores (p < 0.05), whereas magnesium did not. Vitamin D was significantly negatively correlated with the pain and function subscales (p < 0.01), and magnesium was negatively correlated with the stiffness subscale (p < 0.05). Cut-off points for differentiating mild-moderate and severe WOMAC scores were 18.42 ng/ml for vitamin D (AUC 0.833, sensitivity 88.9%, specificity 69.2%) and 1.945 mmol/L for magnesium (AUC 0.634, sensitivity 88.9%, specificity 40.4%). Conclusion. Compared to magnesium, vitamin D showed a significant negative correlation with total WOMAC scores, as well as the pain and function subscales, indicating a stronger association with functional outcomes in KOA. Its identified cut-off point effectively differentiates mild-moderate from severe WOMAC classifications. However, magnesium had a correlation with the stiffness subscale, a relationship not observed with vitamin D.
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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 | 0.001 | 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 | 0.001 | 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".