38% silver diamine fluoride vs 5,000-ppm F (1.1% NaF) toothpaste or gel: Arrest or reversal of noncavitated and cavitated root carious lesions
- Population
- Adults (including institutionalized/older adults) with noncavitated and cavitated carious lesions on root surfaces (permanent teeth)
- Intervention
- 38% silver diamine fluoride
- Comparison
- 5,000-ppm F (1.1% NaF) toothpaste or gel
- Outcome
- Arrest or reversal of noncavitated and cavitated root carious lesions
38% SDF solution (applied annually) may not differ from 5,000-ppm F (1.1% NaF) toothpaste or gel for arrest or reversal of root carious lesions (RR 0.72, 95% CI 0.18 to 2.95; very low certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
38% SDF solution (applied annually) vs 5,000-ppm F (1.1% NaF) toothpaste or gel Arrest or reversal of noncavitated and cavitated root carious lesions · Adults (including institutionalized/older adults) with noncavitated and cavitated carious lesions on root surfaces… · 3-12 mo, Dental practice (professionally applied or prescribed nonrestorative caries treatments; parallel and split-mouth RCTs) 38% SDF solution (applied annually) may not differ from 5,000-ppm F (1.1% NaF) toothpaste or gel for arrest or reversal of root carious lesions (RR 0.72, 95% CI 0.18 to 2.95; very low certainty). Nonrestorative Treatments for Caries: Systematic Review and Network Meta-analysis. (2019) All outcomes | RR 0.72 [0.18, 2.95] | 7 studies · 1304 participants | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Nonrestorative Treatments for Caries: Systematic Review and Network Meta-analysis. 2019 All outcomes | June 2017 | 54 | Critically Low / Critically Low |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
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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.