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Record W3191608946 · doi:10.1159/000517514

Association between Vitamin D Level and Acne, and Correlation with Disease Severity: A Meta-Analysis

2021· review· en· W3191608946 on OpenAlexaboutno aff
Yusuf Hasamoh, Kunlawat Thadanipon, Premjit Juntongjin

Bibliographic record

VenueDermatology · 2021
Typereview
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsAcneMedicineMeta-analysisVitamin D and neurologyCorrelationDiseaseDermatologySeverity of illnessAssociation (psychology)Internal medicinePsychologyMathematics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.239
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.345
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations13
Published2021
Admission routes1
Has abstractyes

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