Epilepsy (as exposure/condition) vs Healthy participants without epilepsy (control group): Caries in primary teeth: dmft (3 years)
- Population
- people with epilepsy
- Intervention
- Epilepsy (as exposure/condition)
- Comparison
- Healthy participants without epilepsy (control group)
- Outcome
- Caries in primary teeth: dmft (3 years)
The dmft (primary-teeth caries) index does not differ significantly between people with epilepsy and controls (SMD 0.132, 95% CI -0.22 to 0.484; high certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Epilepsy (as exposure/condition) vs Healthy participants without epilepsy (control group) dmft (decayed, missing, filled primary teeth) · People with epilepsy (children, adolescents, and adults) · Clinical/community dental examination; multiple countries (England, Turkey, Egypt, Iran, China, India) The dmft (primary-teeth caries) index does not differ significantly between people with epilepsy and controls (SMD 0.132, 95% CI -0.22 to 0.484; high certainty). Evaluating the DMFT and dmft indices in people with epilepsy: A systematic review and meta-analysis. (2025) All outcomes | SMD 0.132 [-0.22, 0.484] | 5 studies | High |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Evaluating the DMFT and dmft indices in people with epilepsy: A systematic review and meta-analysis. 2025 All outcomes | Up to October 30, 2024 | 12 | Not applicable |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Epilepsy (as exposure/condition) vs Healthy controls · Children and adolescents with epilepsy · 1 review
- Epilepsy (as exposure/condition) vs Healthy participants without epilepsy (control group) · Children and adolescents with epilepsy · 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.