Resin sealant (one-time) vs Control (water): New coronal caries in permanent molars (caries prevention)
Resin sealant gave a 65% prevented fraction (fissure site) vs water, the highest fissure-site value (p<0.002; ungraded).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Resin sealant (one-time) vs Control (water) New coronal caries in permanent molars (caries prevention) · Children with dental caries in permanent (first) molars · 24 months, School-based (children), Liu 2012 (resin sealant, fissure site) Resin sealant gave a 65% prevented fraction (fissure site) vs water, the highest fissure-site value (p<0.002; ungraded). A systematic review on the effect of silver diamine fluoride for management of dental caries in permanent… (2023) All outcomes | Prevented Fraction 65 | 1 study · 501 participants | GRADE not reported |
Resin sealant (one-time) vs Control (water) New coronal caries in permanent molars (caries prevention) · Children with dental caries in permanent (first) molars · 24 months, School-based (children), Liu 2012 (resin sealant, tooth level) Resin sealant gave a 60% prevented fraction (tooth level) for caries in children's permanent molars vs water (p<0.04; ungraded). A systematic review on the effect of silver diamine fluoride for management of dental caries in permanent… (2023) All outcomes | Prevented Fraction 60 | 1 study · 501 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| A systematic review on the effect of silver diamine fluoride for management of dental caries in permanent teeth. 2023 All outcomes | December 2022 | 13 | Low / Critically Low |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.