Bleaching before resin infiltration (bleaching + infiltration) vs Resin infiltration alone: Masking effect (esthetic improvement)
- Population
- Patients with dental fluorosis
- Intervention
- Bleaching before resin infiltration (bleaching + infiltration)
- Comparison
- Resin infiltration alone
- Outcome
- Masking effect (esthetic improvement)
Bleaching before resin infiltration did not improve masking of fluorosis compared with infiltration alone (MD -0.30, 95% CI -0.98 to 0.39; moderate certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Bleaching before resin infiltration (bleaching + infiltration) vs Resin infiltration alone Masking effect (esthetic improvement) · Patients with dental fluorosis Bleaching before resin infiltration did not improve masking of fluorosis compared with infiltration alone (MD -0.30, 95% CI -0.98 to 0.39; moderate certainty). Efficacy of resin infiltration to mask post-orthodontic or non-post-orthodontic white spot lesions or… (2021) All outcomes | MD -0.30 [-0.98, 0.39] | 2 studies | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Efficacy of resin infiltration to mask post-orthodontic or non-post-orthodontic white spot lesions or fluorosis - a systematic review and… 2021 All outcomes | Not specified | 11 | Critically Low / Critically Low |
Studies behind the findings
The primary studies the full-text reviews tie to this outcome. Reviews with headline outcomes only do not list them here.
- Power bleaching enhances resin infiltration masking effect of dental fluorosis. A randomized clinical trial · 2018 · included by 1 of these review
- Comparative evaluation of esthetic changes in nonpitted fluorosis stains when treated with resin infiltration, in‐office bleaching, and… · 2017 · included by 1 of these review
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.