Question · asked by 1 review

Resin infiltration vs Fluoride varnish: Remineralization / reduction in lesion severity (change in QLF, laser fluorescence, or lesion area)

Population
Patients with white spot lesions / early caries lesions (WSLs/ECLs), including orthodontic and non-orthodontic lesions, active caries lesions, MIH, and artificial in vitro lesions; predominantly children and adolescents
Intervention
Resin infiltration
Comparison
Fluoride varnish
Outcome
Remineralization / reduction in lesion severity (change in QLF, laser fluorescence, or lesion area)

Resin infiltration was significantly better than fluoride varnish (SMD -0.70, 95% CI -1.18 to -0.21); certainty of evidence not assessed (no GRADE).

What each review found

Include earlier review versions
FindingEffectStudiesGRADE certainty
Resin infiltration vs Fluoride varnish (gold standard)
Remineralization / reduction in lesion severity (change in QLF, laser fluorescence, or lesion area) · Patients with white spot lesions / early caries lesions (WSLs/ECLs), including orthodontic and non-orthodontic… · RCTs (clinical and in vitro); predominantly children and adolescents; orthodontic and non-orthodontic white spot lesions, early caries lesions, and artificial lesions
Resin infiltration was significantly better than fluoride varnish (SMD -0.70, 95% CI -1.18 to -0.21); certainty of evidence not assessed (no GRADE).
Comparison of therapies of white spot lesions: a systematic review and network meta-analysis. (2023) All outcomes
SMD -0.70 [-1.18, -0.21]4 studiesGRADE not reported

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

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Comparison of therapies of white spot lesions: a systematic review and network meta-analysis.
2023 All outcomes
July 2022 (last search reported in abstract); search window January 2007 to June 2022 (Methods)81Low / 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.