Scandinavian and North American Moist Snuff and Periodontitis: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
AIM: To answer the focused PECOS question: in humans (P), what is the effect of Scandinavian or North American moist snuff (MS) (E), in comparison to non-use (C), in terms of periodontitis (O) as demonstrated in clinical studies (S)? METHODS: Electronic databases (MEDLINE, EMBASE and Cochrane) and grey literature were searched for relevant studies reporting clinical and/or patient-reported periodontal outcomes. Qualitative and quantitative syntheses (random-effects meta-analysis with pooled odds ratios [ORs] or effect sizes [ESs] and 95% confidence intervals [CIs]) were performed to determine the associations between MS use and primary (periodontitis) or secondary outcomes (gingival recession, gingivitis). Risk of bias (Newcastle-Ottawa scale) and certainty of evidence (GRADE) were assessed. RESULTS: Twenty-two mostly cross-sectional studies from Sweden (n = 11), the United States (n = 10) and Norway (n = 1) were included. MS use was most frequently associated with buccal recession. Qualitatively, an association between MS use and periodontitis (n = 16) was judged to be unlikely. Based on studies with high clinical heterogeneity, no significant associations were found between MS use and periodontitis (n = 2 [12,775 participants], OR = 1.49 [CI: 0.71-3.16]), recessions (n = 9 [3719 participants], ES = -0.04 [CI: -0.98 to 0.90]) or gingivitis (n = 3 [1429 participants], ES = 0.09 [CI: -0.36 to 0.55]). The certainty of evidence was judged to be very low. CONCLUSION: The current evidence, mostly based on cross-sectional studies and very low certainty, suggests that Scandinavian or North American MS use is not associated with periodontitis. PROSPERO: CRD42023417652.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".