Question · asked by 1 review

Glass ionomer cement (for bracket bonding) vs Resin adhesive: Initiation of white spot lesions (WSL), visual-tactile assessment

Population
Patients of any age (11-40 years) receiving comprehensive/fixed orthodontic treatment with fixed appliances
Intervention
Glass ionomer cement (for bracket bonding)
Comparison
Resin adhesive
Outcome
Initiation of white spot lesions (WSL), visual-tactile assessment

There is no clear difference in WSL initiation between glass ionomer cement and resin adhesive for bracket bonding (RR 0.72, not significant); certainty of evidence is very low.

What each review found

Include earlier review versions
FindingEffectStudiesGRADE certainty
Glass ionomer cement (for bracket bonding) vs Resin adhesive (for bracket bonding)
Initiation of white spot lesions (WSL), visual-tactile assessment · Patients of any age (11-40 years) receiving comprehensive/fixed orthodontic treatment with fixed appliances · 12-24 months follow-up, Patients undergoing fixed (multibracket) orthodontic appliance treatment; clinical/dental setting; analysis at tooth level
There is no clear difference in WSL initiation between glass ionomer cement and resin adhesive for bracket bonding (RR 0.72, not significant); certainty of evidence is very low.
Efficacy of sealants and bonding materials during fixed orthodontic treatment to prevent enamel… (2021) All outcomes
RR 0.72 [0.34, 1.54]3 studies · 394 participantsVery low

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

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Efficacy of sealants and bonding materials during fixed orthodontic treatment to prevent enamel demineralization: a systematic review and…
2021 All outcomes
Not specified (no date restriction on language or year)24Critically 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.

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.