Association entre riboflavine, folates, vitamine B6, vitamine B12 et maladie parodontale : revue systématique de la littérature
Bibliographic record
Abstract
Objective: the aim was to explore the association between dietary intakes or circulating levels of riboflavin (B2), folates, vitamin B6, and vitamin B12 and periodontal disease. Methods: for this systematic review, PubMed, Scopus, and Web of Science were searched on October 11, 2023. Two blinded reviewers selected observational studies focusing on the association between at least one of the B vitamins involved in the methionine-homocysteine cycle (B2, B6, folates, B12) and the presence of periodontal parameters associated with periodontal disease. The risk of bias was assessed using the Newcastle-Ottawa Scale. Results: out of 651 eligible references, 8 were included: 6 cross-sectional, 1 case-control, and 1 prospective cohort studies. Higher levels of folates (2 out of 4 studies), vitamin B2 (2 out of 5 studies), and vitamin B12 (1 out of 3 studies) were associated with lower risk of periodontal diseases. No significant association was observed with vitamin B6. The included cross-sectional studies were of low quality, while the case-control and cohort studies were of relatively good quality. Conclusion: the results reveal heterogeneity in the associations for all vitamins studied. Longitudinal and controlled studies are necessary to clarify these associations and define precise nutritional recommendations for the prevention and management of periodontal disease.
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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 | 0.020 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".