Question · asked by 1 review

Silver diamine fluoride (SDF) vs Other methods (pooled: ART/glass ionomer cement, nano-silver fluoride, sodium fluoride varnish): Caries arrestment at the tooth level

Population
Children and adults with active dental caries (aged 1-50; mostly preschool/school children with primary dentition)
Intervention
Silver diamine fluoride (SDF)
Comparison
Other methods (pooled: ART/glass ionomer cement, nano-silver fluoride, sodium fluoride varnish)
Outcome
Caries arrestment at the tooth level

SDF probably results in a slight increase in tooth-level caries arrestment versus other methods (moderate certainty).

What each review found

Include earlier review versions
FindingEffectStudiesGRADE certainty
Silver diamine fluoride (SDF; 38% in most trials, 30% in three) vs Other methods (pooled: ART/glass ionomer cement, nano-silver fluoride, sodium fluoride varnish)
Caries arrestment at the tooth level · Children and adults with active dental caries (aged 1-50; mostly preschool/school children with primary dentition) · 6 to 12 months, Children/adults with dental caries; multiple countries; community/clinic care setting not clearly specified, Overall (all comparators pooled)
SDF probably results in a slight increase in tooth-level caries arrestment versus other methods (moderate certainty).
The role of silver diamine fluoride as dental caries preventive and arresting agent: a systematic review and… (2024) All outcomes
OR 1.74 [0.88, 3.46]5 studies · 743 participantsModerate

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
The role of silver diamine fluoride as dental caries preventive and arresting agent: a systematic review and meta-analysis.
2024 All outcomes
Not specified (publication window 2014-2024; references accessed July 2024)20Critically Low / Critically Low

The same intervention and outcome, asked in another population or against another comparator.

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.