Question · asked by 1 review

Dental caries (ECC/severe ECC) as exposure/grouping vs Caries-free controls: Relative abundance of S. mutans in saliva

Population
Individuals assessed for dental caries, predominantly children with early childhood caries (ECC) or severe ECC (age about 1 to 4 years)
Intervention
Dental caries (ECC/severe ECC) as exposure/grouping
Comparison
Caries-free controls
Outcome
Relative abundance of S. mutans in saliva

A few small studies report Streptococcus mutans relative abundance in caries versus caries-free children without pooling; the evidence is ungraded and not meta-analyzed.

What each review found

Current versions only
FindingEffectStudiesGRADE certainty
Dental caries (ECC/severe ECC) as exposure/grouping vs Caries-free controls
Relative abundance of Streptococcus mutans · Individuals assessed for dental caries, predominantly children with early childhood caries (ECC) or severe ECC (age… · Community and clinical pediatric dental settings (USA, Hong Kong, Indonesia); saliva or dental plaque microbial sampling
A few small studies report Streptococcus mutans relative abundance in caries versus caries-free children without pooling; the evidence is ungraded and not meta-analyzed.
A systematic review of Streptococcus Mutans and Veillonellae species interactions in dental caries… (2025) All outcomes
Reported in 2 studies without pooling: Agnello 2017 median S. mutans relative abundance 0.73% (0.02-22.9) in caries vs 0.15% (0.006-10.4) in controls; Chalmers 2015 Streptococcus 35.63+/-17.04 (caries) vs 32.11+/-18.91…1 study · 50 participantsGRADE not reported

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

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
A systematic review of Streptococcus Mutans and Veillonellae species interactions in dental caries progression: Positive or Negative impact?
2024 All outcomes
18 July 2023 (databases searched from inception)7Not 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.