25-Hydroxyvitamin D Levels and Vitamin D Deficiency in Children with Rheumatologic Disorders and Controls
Bibliographic record
Abstract
OBJECTIVE: To evaluate the prevalence of vitamin D deficiency, as well as factors associated with serum 25-hydroxyvitamin D [25(OH)D] levels, in children attending a pediatric rheumatology clinic, and to determine whether there was a difference in serum 25(OH)D levels and in vitamin D deficiency between children with autoimmune disorders and nonautoimmune conditions. METHODS: Cross-sectional analysis of serum 25(OH)D levels of patients between the ages of 2 and 19 years, seen between November 2008 and October 2009. RESULTS: A total of 254 patients were studied (169 autoimmune disorders, 85 nonautoimmune conditions). The mean age of study patients was 12.3 years; 67% were female and 80% were white. In the autoimmune disorders group, 23% had vitamin D deficiency [serum 25(OH)D < 20 ng/ml], and in the nonautoimmune conditions group 14% were vitamin D deficient. The average level of serum 25(OH)D was 28.6 (± 11) ng/ml (range 2 to 59). Age, ethnicity, body mass index, use of supplements, and season were significantly associated with serum levels of 25(OH)D (all p ≤ 0.02). The OR of patients with autoimmune disorders being vitamin D deficient was 2.3, in relation to patients with nonautoimmune conditions (p = 0.04). CONCLUSION: Twenty percent of patients attending a pediatric rheumatology clinic were vitamin D deficient. Patients with autoimmune disorders were more likely to be vitamin D deficient than patients with nonautoimmune conditions. Screening of serum 25(OH)D levels should be performed for patients with autoimmune disorders.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".