Mineral trioxide aggregate (MTA) vs Root repair material (RRM): Success rate at 1 year
- Population
- Patients needing retrograde filling in root canal therapy (orthograde root canal filling or retreatment not possible; periapical surgery used to save the tooth); no age or gender limitations
- Intervention
- Mineral trioxide aggregate (MTA)
- Comparison
- Root repair material (RRM)
- Outcome
- Success rate at 1 year
It is very uncertain whether mineral trioxide aggregate (MTA) changes success rate at 1 year compared with root repair material (RRM) (very low certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Mineral trioxide aggregate (MTA) vs Root repair material (RRM) Success rate at 1 year · Patients needing retrograde filling in root canal therapy (orthograde root canal filling or retreatment not possible;… · 1 year It is very uncertain whether mineral trioxide aggregate (MTA) changes success rate at 1 year compared with root repair material (RRM) (very low certainty). Materials for retrograde filling in root canal therapy (2021) · Cochrane All outcomes | RR 1.00 [0.94, 1.07] | 2 studies | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Materials for retrograde filling in root canal therapy 2021 · Cochrane All outcomes | 2021-04 | Not listed | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Mineral trioxide aggregate (MTA) vs Intermediate restorative material (IRM) · Patients needing retrograde filling in root canal therapy (orthograde root canal filling… · 1 review
- Mineral trioxide aggregate (MTA) vs Super ethoxybenzoic acid (Super-EBA) · Patients needing retrograde filling in root canal therapy (orthograde root canal filling… · 1 review
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.