Relationship between Serum Magnesium Concentration and Radiographic Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To establish whether there is a relationship between serum magnesium (Mg) concentration and radiographic knee osteoarthritis (OA). METHODS: There were 2855 subjects in this cross-sectional study. Serum Mg concentration was measured using the chemiluminescence method. Radiographic OA of the knee was defined as changes consistent with Kellgren-Lawrence (K-L) grade 2 on at least 1 side. Mg concentration was classified into 1 of 4 quartiles: ≤ 0.87, 0.88-0.91, 0.92-0.96, or ≥ 0.97 mmol/l. Multivariable logistic analysis was used to test the association between serum Mg and radiographic knee OA after adjustment for potentially confounding factors. The OR with 95% CI for the association between radiographic knee OA and serum Mg concentration were calculated for each quartile. The quartile with the lowest value was regarded as the reference category. RESULTS: Significant association between serum Mg concentration and radiographic knee OA was observed in the model after adjustment for age, sex, and body mass index, as well as in the multivariable model. The multivariable-adjusted OR (95% CI) for radiographic knee OA in the second, third, and fourth serum Mg concentration quartiles were 0.90 (95% CI 0.71-1.13), 0.92 (95% CI 0.73-1.16), and 0.72 (95% CI 0.57-0.92), respectively, compared with the lowest (first) quartile. A clear trend (p for trend was 0.01) was observed. The relative odds of radiographic knee OA was decreased by 0.72 times in the fourth serum Mg quartile compared with the lowest quartile. CONCLUSION: Serum Mg concentration may have an inverse relationship with radiographic OA of the knee.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".