The impact of vaping on periodontitis: A systematic review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: While tobacco cigarette smoking has been proven to be a risk factor for periodontitis, limited information is available regarding vaping, a new alternative to smoking that has been branded as less harmful. Several important in vitro studies have shown that vaping has a similarly damaging effect as cigarette smoking on the health of the periodontium. However, a comprehensive review is lacking in this field. Therefore, we aimed to systematically review the literature about the impact of vaping on periodontitis. METHODS: The research question was created using the PICOs format. A systematic search of the following electronic databases was performed up to March 2020: Medline, Embase, PubMed, Cochrane, and grey literature. Human studies that assessed periodontal status (plaque index, bleeding on probing, clinical attachment loss, marginal bone loss, and probing depth) in e-cigarette users compared to non-smokers (control group) were assessed based on an estimate of fixed effects. The weights of the studies were calculated based on their risks of bias. RESULTS: After duplicates were removed, 1,659 studies were screened and 8 case-control studies that investigated the relationship between vaping and periodontal parameters in humans were selected after their risk of bias assessment. Estimated effects of vaping after weighting results based on their standard deviation showed increased plaque, marginal bone loss, clinical attachment loss, pocket depth, and reduced bleeding on probing. CONCLUSION: This study concluded that there is not enough evidence to fully characterize the impacts of vaping on periodontitis. However, within the limitations of our review and the selected included studies, the available results point to increased destruction of the periodontium leading to the development of the 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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".