Question · asked by 1 review
Fixed orthodontic treatment with fixed (multibracket) appliances (exposure) vs None (single-group prevalence/incidence estimate): Prevalence of ICLs (mean number of lesions per subject)
- Population
- Patients (permanent dentition) during or after fixed orthodontic treatment with fixed (multibracket) appliances
- Intervention
- Fixed orthodontic treatment with fixed (multibracket) appliances (exposure)
- Comparison
- None (single-group prevalence/incidence estimate)
- Outcome
- Prevalence of ICLs (mean number of lesions per subject)
Patients had on average about 2.24 ICLs per subject during/after fixed orthodontic treatment (95% CI 1.79-2.70; very low certainty; very high heterogeneity).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Fixed orthodontic treatment with fixed (multibracket) appliances (exposure) vs None (single-group prevalence/incidence estimate) Prevalence of ICLs (mean number of lesions per subject) · Patients (permanent dentition) during or after fixed orthodontic treatment with fixed (multibracket) appliances · During or after fixed orthodontic treatment (cross-sectional/at debonding), International (16 countries; studies published 2005-2022); orthodontic clinical settings, Overall (random-effects model) Patients had on average about 2.24 ICLs per subject during/after fixed orthodontic treatment (95% CI 1.79-2.70; very low certainty; very high heterogeneity). Distribution of initial caries lesions in relation to fixed orthodontic therapy. A systematic review and… (2024) All outcomes | MEAN 2.24 [1.79, 2.70] | 6 studies · 484 participants | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Distribution of initial caries lesions in relation to fixed orthodontic therapy. A systematic review and meta-analysis. 2024 All outcomes | 01 May 2023 | 33 | Not applicable |
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.