Double primary (canine and first molar) tooth extraction vs Single primary (canine) tooth extraction: Number of participants referred for surgical exposure of the PDC
- Population
- Young people aged 9 to 14 years diagnosed with one or both palatally displaced permanent maxillary canines (PDC)
- Intervention
- Double primary (canine and first molar) tooth extraction
- Comparison
- Single primary (canine) tooth extraction
- Outcome
- Number of participants referred for surgical exposure of the PDC
It is very uncertain whether double primary (canine and first molar) tooth extraction changes number of participants referred for surgical exposure of the PDC compared with single primary (canine) tooth extraction (very low certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Double primary (canine and first molar) tooth extraction vs Single primary (canine) tooth extraction Number of participants referred for surgical exposure of the PDC · Young people aged 9 to 14 years diagnosed with one or both palatally displaced permanent maxillary canines (PDC) · 48 months (maximum; mITT) It is very uncertain whether double primary (canine and first molar) tooth extraction changes number of participants referred for surgical exposure of the PDC compared with single primary (canine) tooth extraction (very low certainty). Interventions for promoting the eruption of palatally displaced permanent canine teeth, without the need for… (2021) · Cochrane All outcomes | RR 0.31 [0.06, 1.45] | 2 studies · 96 participants | Very low |
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.