Evaluation of IL‐6 levels and +3954 polymorphism of IL‐1β in burning mouth syndrome: A systematic review and meta‐analysis
Bibliographic record
Abstract
This study evaluated IL-6 salivary levels as well as the +3954 polymorphism of IL-1β in patients with burning mouth syndrome and healthy individuals, through case-control studies. This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We conducted this research in PubMed/MEDLINE, Cochrane Library and Web of Science databases. The risk of bias was measured based in the Newcastle-Ottawa Scale. Researches with a group of patients with burning mouth syndrome and a control group in which the presence of the +3954 polymorphism of IL-1β and/ or IL-6 salivary levels through non-stimulated saliva were evaluated to detect if this interleukin concentrations are increased in patients and if the polymorphism is a risk factor for this syndrome. We identified seven studies with total of 440 participants, 229 patients with burning mouth syndrome and 211 healthy controls, ages 24-84 years old. The female gender was predominant. Patients in the majority of studies did not present increased levels of IL-6 and the +3954 polymorphism of IL-1β is not a risk factor for this syndrome. A few studies researched biomarkers in this pathology and more investigations are required not only to identify salivary levels and the polymorphism evaluated, but also other interleukins and polymorphisms in order to clarify the etiopathogenesis of this syndrome as well as for propose new diagnostic methods and treatments.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".