Association between Vitamin D Level and Acne, and Correlation with Disease Severity: A Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Vitamin D deficiency is frequently associated with several medical conditions. However, a comprehensive meta-analysis assessing the association between vitamin D level and acne is lacking. OBJECTIVE: To determine the relationship between vitamin D level and acne, and to assess the association between vitamin D level and acne severity. METHODS: This meta-analysis was assessed by using the PubMed, EMBASE, Cochrane, and Scopus databases following the PRISMA guidelines. Serum/plasma 25-hydroxyvitamin D (25[OH]D) level, vitamin D deficiency, and the severity association between acne patients and healthy controls (HCs) were evaluated. The quality assessment was performed by using the Newcastle-Ottawa Scale. RESULTS: Thirteen articles with a total of 1,362 acne patients and 1,081 HCs were included. The circulating 25(OH)D levels were significantly lower in patients with acne than in HCs (pooled MD = -9.02 ng/mL, 95% CI = -13.22 to -4.81, p < 0.0001). Vitamin D deficiency was more prevalent in acne patients than in HCs (pooled OR = 2.97, 95% CI = 1.68-5.23, I2 = 72%). Also, vitamin D levels were negatively correlated with acne severity. CONCLUSION: This meta-analysis demonstrated the significantly low vitamin D levels in acne patients. Also, there was evidence of an inverse association between vitamin D levels and acne severity. Therefore, vitamin D might be involved in the pathogenesis of acne.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.055 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".