Question · asked by 1 review

Ion-releasing restoration (glass ionomer-based and compomer/polyacid-modified composite) vs Resin composite restoration: Secondary caries (caries around restorations), load-bearing cavities

In load-bearing cavities, ion-releasing (GIC and compomer) and resin composite restorations show no significant difference in secondary caries (RD -0.00, 95% CI -0.01 to 0.01; not GRADE-rated).

What each review found

Include earlier review versions
FindingEffectStudiesGRADE certainty
Ion-releasing restoration (glass ionomer-based and compomer/polyacid-modified composite) vs Resin composite restoration
Secondary caries (caries around restorations), load-bearing cavities · Patients with permanent dentition in need of restorations in load-bearing cavities (Class I/II posterior) · Last reported follow-up (2-3 years), Permanent dentition; university (majority), school, and private-practice settings across multiple countries (Turkey, Brazil, Sweden, India, Vietnam, Belgium, Germany, etc.)
In load-bearing cavities, ion-releasing (GIC and compomer) and resin composite restorations show no significant difference in secondary caries (RD -0.00, 95% CI -0.01 to 0.01; not GRADE-rated).
Secondary caries and marginal adaptation of ion-releasing versus resin composite restorations: a systematic… (2022) All outcomes
RD -0.00 [-0.01, 0.01]6 studies · 883 participantsGRADE not reported

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

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Secondary caries and marginal adaptation of ion-releasing versus resin composite restorations: a systematic review and meta-analysis of…
2022 All outcomes
21 May 2021 (databases searched until 21 May 2021; no date or language restriction)37Critically Low / Critically Low

Studies behind the findings

None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.

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.