Question · asked by 0 reviews

Single-visit root canal treatment vs Multiple-visit root canal treatment (two or more visits): Radiological failure (periapical radiolucency) after at least 1 year

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
Radiological failure (periapical radiolucency) after at least 1 year

Single-visit root canal treatment showed no clear difference in radiological failure (periapical radiolucency) after at least 1 year compared with multiple-visit root canal treatment (two or more visits); GRADE not reported.

What each review found

Current versions only
FindingEffectStudiesGRADE certainty
Single-visit root canal treatment vs Multiple-visit root canal treatment (two or more visits)
Radiological failure (periapical radiolucency) after at least 1 year · People aged over 10 years requiring root canal treatment; permanent teeth with completely formed apex and without… · At least 1 year (range 1 to 5 years)
Single-visit root canal treatment showed no clear difference in radiological failure (periapical radiolucency) after at least 1 year compared with multiple-visit root canal treatment (two or more visits); GRADE not reported.
Single versus multiple visits for endodontic treatment of permanent teeth (2007) · Cochrane All outcomesearlier version CD005296.PUB2, superseded
RR 0.85 [0.59, 1.23]5 studies · 657 participantsGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Single versus multiple visits for endodontic treatment of permanent teeth
2022 · Cochrane All outcomes
25 April 2022Not listedNot assessed

The same intervention and outcome, asked in another population or against another comparator.

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.