Question · asked by 1 review
Fixed orthodontic treatment with fixed (multibracket) appliances (exposure) vs None (single-group prevalence/incidence estimate): Incidence of new ICLs (mean number of new lesions per subject)
- Population
- Patients undergoing fixed orthodontic treatment with fixed (multibracket) appliances, followed for development of new ICLs
- Intervention
- Fixed orthodontic treatment with fixed (multibracket) appliances (exposure)
- Comparison
- None (single-group prevalence/incidence estimate)
- Outcome
- Incidence of new ICLs (mean number of new lesions per subject)
Patients developed on average about 2.29 new ICLs during fixed orthodontic treatment (95% CI 1.12-3.46; very low certainty; very high heterogeneity).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Fixed orthodontic treatment with fixed (multibracket) appliances (exposure) vs None (single-group prevalence/incidence estimate) Incidence of new ICLs (mean number of new lesions per subject) · Patients undergoing fixed orthodontic treatment with fixed (multibracket) appliances, followed for development of new… · During fixed orthodontic treatment (development of new lesions), International (16 countries; studies published 2005-2022); orthodontic clinical settings, Overall (random-effects model) Patients developed on average about 2.29 new ICLs during fixed orthodontic treatment (95% CI 1.12-3.46; 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 2.29 [1.12, 3.46] | 5 studies · 208 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.