Is vitamin D deficiency associated with non specific musculoskeletal pain?
Bibliographic record
Abstract
BACKGROUNDS: Vitamin D deficiency is common worldwide, including Iran. It has been suggested that vitamin D deficiency is associated with non-specific musculoskeletal pain. The aim of this study is evaluation of the association of musculoskeletal pain with vitamin D deficiency and the response of the patients to vitamin D supplementation. MATERIALS AND METHODS: Sixty two adult patients with chief complaint of musculoskeletal pain were enrolled in the study. Serum concentrations of 25(OH)D, Calcium, Phosphate, Alkaline Phosphatase and PTH were determined. If there was vitamin D deficiency, oral vitamin D supplementation was given. Assessment of pain and its response to therapy was carried out using Visual assessment score (VAS). SPSS software version 15.0 was used for statistical analyses. FINDINGS: Most of the patients (95.4%) had vitamin D deficiency. Pain in 53 patients (85.5%) with responded to the proposed treatment. In responder group post treatment vitamin D concentration was significantly higher than non responder group (60.6±27.6and 39.2±9.6 nmol/l respectively, p<0.01) pretreatment vitamin D and minerals concentrations and pain characteristics did not have significant differences in responder and non responder group. CONCLUSION: Treatment with vitamin D can relieve the pain in majority of the patients with vitamin D deficiency. Lack of response can be due to insufficient increase in serum vitamin D concentration. Reassessment of serum 25(OH)D concentration is recommended in nonresponsive patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".