Question · asked by 1 review
Radiographic caries detection (bitewing radiography) vs Reference standard (histological validation or cavity/lesion opening; advanced = cavitated/dentin-involved lesions, all = enamel-confined initial lesions also counted): Negative LR for detecting advanced occlusal caries
- Population
- Occlusal surfaces of permanent molars (demonstrated in 12-14 year-olds; underlying diagnostic accuracy studies, mostly in vitro)
- Intervention
- Radiographic caries detection (bitewing radiography)
- Comparison
- Reference standard (histological validation or cavity/lesion opening; advanced = cavitated/dentin-involved lesions, all = enamel-confined initial lesions also counted)
- Outcome
- Negative LR for detecting advanced occlusal caries
In the conventional (all-studies) meta-analysis, the negative lr of radiographic detection for advanced occlusal caries was 0.53 (95% CI 0.46 to 0.62) (ungraded).
What each review found
Include earlier review versionsNo studies found 0 · 0%GRADE not reported 3 · 100%Very low 0 · 0%Low 0 · 0%Moderate 0 · 0%High 0 · 0%
| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Radiographic caries detection (bitewing radiography) vs Reference standard (histological validation or cavity/lesion opening; advanced = cavitated/dentin-involved lesions, all = enamel-confined initial lesions also counted) Negative LR for detecting advanced occlusal caries · Occlusal surfaces of permanent molars (demonstrated in 12-14 year-olds; underlying diagnostic accuracy studies, mostly… · Conventional meta-analysis (all studies) In the conventional (all-studies) meta-analysis, the negative lr of radiographic detection for advanced occlusal caries was 0.53 (95% CI 0.46 to 0.62) (ungraded). Visual and radiographic caries detection: a tailored meta-analysis for two different settings, Egypt and… (2018) All outcomes | Negative LR 0.53 [0.46, 0.62] | 44 studies | GRADE not reported |
Radiographic caries detection (bitewing radiography) vs Reference standard (histological validation or cavity/lesion opening; advanced = cavitated/dentin-involved lesions, all = enamel-confined initial lesions also counted) Negative LR for detecting advanced occlusal caries · Occlusal surfaces of permanent molars (demonstrated in 12-14 year-olds; underlying diagnostic accuracy studies, mostly… · Public health clinic, Giza (Cairo), Egypt, Tailored to Egypt In the meta-analysis tailored to Egypt, the negative lr of radiographic detection for advanced occlusal caries was 0.51 (95% CI 0.44 to 0.6) (ungraded). Visual and radiographic caries detection: a tailored meta-analysis for two different settings, Egypt and… (2018) All outcomes | Negative LR 0.51 [0.44, 0.6] | 38 studies | GRADE not reported |
Radiographic caries detection (bitewing radiography) vs Reference standard (histological validation or cavity/lesion opening; advanced = cavitated/dentin-involved lesions, all = enamel-confined initial lesions also counted) Negative LR for detecting advanced occlusal caries · Occlusal surfaces of permanent molars (demonstrated in 12-14 year-olds; underlying diagnostic accuracy studies, mostly… · Private practice, rural northern Germany, Tailored to Germany In the meta-analysis tailored to Germany, the negative lr of radiographic detection for advanced occlusal caries was 0.54 (95% CI 0.46 to 0.63) (ungraded). Visual and radiographic caries detection: a tailored meta-analysis for two different settings, Egypt and… (2018) All outcomes | Negative LR 0.54 [0.46, 0.63] | 36 studies | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Visual and radiographic caries detection: a tailored meta-analysis for two different settings, Egypt and Germany. 2018 All outcomes | Not specified (data reused from two source systematic reviews, Gimenez 2015 and Schwendicke 2015) | 2 | 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.