Is there a risk of harm or toxicity in the placement of pit and fissure sealant materials? A systematic review.
Bibliographic record
Abstract
BACKGROUND: Recently, there has been increased interest in the in vivo release of dental sealant components, such as bisphenol A (BPA), which has the potential to bind the estrogen receptors of relevant cells at subtoxic concentrations in vitro, impairing the development, health and reproductive systems of wildlife. The purpose of this systematic review was to investigate whether the placement of pit and fissure sealant materials causes toxicity, and thus harms patients. METHODS: The literature search (from the earliest record up to March 2007) for relevant articles was done with Ovid MEDLINE, CINAHL and other bibliographic databases. RESULTS: A total of 377 articles were identified by the literature search; relevance was determined by examining the title and abstract of the articles. Eleven original studies met the inclusion criteria. These articles were read in full and scored independently by 2 reviewers. RECOMMENDATIONS: The evidence suggests that patients are not at risk for exposure to BPA from the use of dental sealants. To reduce the potential, if any, for BPA toxicity from sealants, dental providers should use a mild abrasive, such as pumice, either on a cotton applicator or in a prophy cup; have older children and adolescents gargle with tepid water for 30 seconds; or wash the sealant surface for 30 seconds with an air-water syringe while suctioning fluids and debris from a child"s mouth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".