The Relationship Between Iron and Zinc Deficiency and Aphthous Stomatitis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Recurrent aphthous stomatitis (RAS) is known as the most common ulcerative lesion in the oral mucosa. Aphthous has an unknown etiology and is considered a multifactorial disease. This study was conducted to investigate the relationship between iron and zinc deficiency and the occurrence of RAS. Materials and Methods: This systematic review and metaanalysis was performed according to the Preferred Reporting Items for Systematic Reviews and Metaanalyses (PRISMA) guidelines. Data were obtained through an electronic search in international databases, including PubMed, Medline, Embase, ISI Web of Science, Scopus, Springer, ProQuest, ScienceDirect, Clinical Key, and Google Scholar, and domestic Persian databases, including SID, Magiran, and Iran Medex, until April 2021. New-castle Ottawa Scale (NOS) was used to determine the eligibility of studies by evaluating the title and summary of the articles and a partial evaluation of the full text. Comprehensive Metaanalysis (CMA) software was used for data analysis. Results: Initially, a total of 1383 articles were retrieved, of which 941 were duplicate studies. Further, 384 studies were excluded after evaluation of the title and abstract, and 36 studies were excluded after considering the inclusion and exclusion criteria. Finally, 22 articles were included in the metaanalysis. The standardized mean difference value was -0.421 (-0.623--0.20) for iron factor, -0.309 (-0.463--0.154) for iron factor in men, -0.483 (-0.375--0373) for iron factor in women, and -0.955 (-0.282--1.628) for the zinc factor. Conclusion: In general, the serum iron level (in general, in male and female patients separately) and the zinc serum level in patients with RAS were significantly lower than those of healthy people.
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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 | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.044 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".