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Record W4387296155 · doi:10.1002/cre2.794

Serum level of vitamin D in patients with recurrent aphthous stomatitis: A systematic review and meta‐analysis of case control studies

2023· review· en· W4387296155 on OpenAlexaboutno aff
Roya Safari‐Faramani, Mohsen Salehi, Saman Ghambari Haji Shore, Neda Omidpanah

Bibliographic record

VenueClinical and Experimental Dental Research · 2023
Typereview
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
FundersKermanshah University of Medical Sciences
KeywordsEtiologyRecurrent aphthous stomatitisMedicineCochrane LibraryMeta-analysisInternal medicineVitamin D and neurologySystematic reviewvitamin D deficiencyStomatitisGastroenterologyMEDLINEDermatologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: Recurrent aphthous stomatitis (RAS) is an ulcerative condition with unknown etiology. The effect of vitamin D in the etiology of RAS is still a matter of controversy. In this study, we aimed at review the available evidence on the role of vitamin D deficiency in RAS etiology. MATERIAL AND METHODS: PubMed, Cochrane Library for Systematic Reviews, ISI Web of Science, Scopus, and EmBase were systematically searched for evidence on RAS and vitamin D up to January 2020. Retrieved records were screened and assessed by two of the authors independently. Newcastle-Ottawa scale was used to assess the quality of individual studies. AMSTAR tool was used for assessing the quality of the study. RESULTS: Eight studies including 383 healthy control and 352 patients with RAS were eligible for the meta-analysis. Serum vitamin D levels were significantly lower in RAS patients. The weighted mean difference was -7.90 (95% CI: -11.96 to -3.85). CONCLUSIONS: The results highlighted the importance of vitamin D deficiency in the etiology of RAS. However, more studies are needed to reach a robust decision. The observed association between vitamin D and RAS is probably due to the effect of vitamin D on the immune system.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0120.001
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.537
GPT teacher head0.590
Teacher spread0.053 · 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.

Study designSystematic review
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

Citations7
Published2023
Admission routes1
Has abstractyes

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