Effects of Vitamin D levels and supplementation on atopic dermatitis: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin condition affecting 5%-20% of children worldwide. Studies suggested both a correlation between serum vitamin D (VD) levels and AD severity and a therapeutic potential role for VD supplementation. OBJECTIVES: To determine whether serum VD levels correlate with AD severity and the effects of supplementation for disease improvement in children. DATA SOURCES: Ovid MEDLINE, EMBASE, and Cochrane Library databases were searched. STUDY SELECTION: Publications with children 0-18 years old with AD and data evaluating effects of VD levels or supplementation on AD severity were included. DATA EXTRACTION: Author, year, inclusion criteria, study design, location, age, VD levels, VD supplementation regimens, and baseline and final disease severities were extracted. RESULTS: Of the 21 included publications, 15, 5, and 1 evaluated VD level, VD supplementation, and both factors with disease severity, respectively. There were 4 randomized control trials (RCTs), 5 cohort, 6 case-control, and 6 cross-sectional studies. A significant inverse correlation between VD level and severity was described in 62.5% (10/16) of studies. There were 67% (4/6) that reported a significant improvement in AD severity with supplementation. LIMITATIONS: Studies meeting inclusion criteria were limited. Furthermore, papers were heterogeneous in terms of location, season, and VD supplementation regimen. Language and publication bias was another potential limitation. CONCLUSION: In children, the majority of existing literature confirmed a link between serum VD levels and AD severity. Weak evidence was found supporting improvement of AD with VD supplementation. Future large-scale studies are needed to support our findings.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it