Question · asked by 0 reviews
Single-visit root canal treatment vs Multiple-visit root canal treatment (two or more visits): Sinus or fistula formation at last
- Population
- People aged over 10 years requiring root canal treatment; permanent teeth with completely formed apex and without internal resorption
- Intervention
- Single-visit root canal treatment
- Comparison
- Multiple-visit root canal treatment (two or more visits)
- Outcome
- Sinus or fistula formation at last
The review found no eligible studies for this question.
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Single-visit root canal treatment vs Multiple-visit root canal treatment (two or more visits) Sinus tract or fistula formation · People aged over 10 years requiring root canal treatment; permanent teeth with completely formed apex and without… The review found no eligible studies for this question. Single versus multiple visits for endodontic treatment of permanent teeth (2007) · Cochrane All outcomesearlier version CD005296.PUB2, superseded | No study reported fistula or sinus track formation | 0 studies | No studies found |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Single versus multiple visits for endodontic treatment of permanent teeth 2022 · Cochrane All outcomes | 25 April 2022 | Not listed | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Single-visit root canal treatment vs Multiple-visit root canal treatment (two or more visits) · People aged 10 years or above requiring root canal treatment; permanent teeth with… · 1 review
- Single-visit root canal treatment vs Multiple-visit root canal treatment (two or more visits) · People receiving endodontic treatment of permanent teeth (aged over 10 years) · 0 reviews
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.