Question · asked by 1 review
High Streptococcus mutans colonization in primary dentition (age 2-3 years) vs Lower Streptococcus mutans load: Caries (DMFT/DMFS) in mixed/permanent dentition
- Population
- School children and adolescents (6-18 years) followed from primary dentition (baseline examination before 72 months of age)
- Intervention
- High Streptococcus mutans colonization in primary dentition (age 2-3 years)
- Comparison
- Lower Streptococcus mutans load
- Outcome
- Caries (DMFT/DMFS) in mixed/permanent dentition
Higher early Streptococcus mutans colonization is associated with more caries in the mixed/permanent dentition (2 studies; not pooled; not GRADE-rated).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
High Streptococcus mutans colonization in primary dentition (age 2-3 years) vs Lower Streptococcus mutans load Caries (DMFT/DMFS) in mixed/permanent dentition · School children and adolescents (6-18 years) followed from primary dentition (baseline examination before 72 months of… · Cohort studies (Netherlands, USA) Higher early Streptococcus mutans colonization is associated with more caries in the mixed/permanent dentition (2 studies; not pooled; not GRADE-rated). Does Early Childhood Caries Increase Caries Development among School Children and Adolescents? A Systematic… (2022) All outcomes | Two studies found a significantly higher DMFT/DMFS score among school children aged 6-12 years who had a higher Streptococcus mutans load at 2-3 years old | 2 studies | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Does Early Childhood Caries Increase Caries Development among School Children and Adolescents? A Systematic Review and Meta-Analysis. 2022 All outcomes | Inception to 28 July 2022 (grey literature accessed 14 September 2022) | 10 | Not applicable |
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.