Extraction of the primary (baby) canine (single primary tooth extraction) vs No extraction (non-intervention control): Root resorption of adjacent permanent teeth caused by the PDC
- Population
- Young people aged 9 to 14 years diagnosed with one or both palatally displaced permanent maxillary canines (PDC)
- Intervention
- Extraction of the primary (baby) canine (single primary tooth extraction)
- Comparison
- No extraction (non-intervention control)
- Outcome
- Root resorption of adjacent permanent teeth caused by the PDC
Extraction of the primary (baby) canine (single primary tooth… showed no clear difference in root resorption of adjacent permanent teeth caused by the PDC compared with no extraction (non-intervention control); GRADE not reported.
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Extraction of the primary (baby) canine (single primary tooth extraction) vs No extraction (non-intervention control) Root resorption of adjacent permanent teeth caused by the PDC · Young people aged 9 to 14 years diagnosed with one or both palatally displaced permanent maxillary canines (PDC) · 12 months Extraction of the primary (baby) canine (single primary tooth… showed no clear difference in root resorption of adjacent permanent teeth caused by the PDC compared with no extraction (non-intervention control); GRADE not reported. Interventions for promoting the eruption of palatally displaced permanent canine teeth, without the need for… (2021) · Cochrane All outcomes | RR 0.60 [0.28, 1.31] | 1 study · 89 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Interventions for promoting the eruption of palatally displaced permanent canine teeth, without the need for surgical exposure, in… 2021 · Cochrane All outcomes | 2021-02 | Not listed | Not assessed |
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.