Question · asked by 1 review
Laser fluorescence (DIAGNOdent 2190/pen) vs Histological validation (serial sectioning, grinding, hemisection, or microradiography): Diagnostic accuracy for occlusal caries detection at the dentin caries detection level (D0-2 versus D3-4)
- Population
- Extracted human permanent posterior teeth (premolars and molars), occlusal (pit-and-fissure) surfaces
- Intervention
- Laser fluorescence (DIAGNOdent 2190/pen)
- Comparison
- Histological validation (serial sectioning, grinding, hemisection, or microradiography)
- Outcome
- Diagnostic accuracy for occlusal caries detection at the dentin caries detection level (D0-2 versus D3-4)
In in vitro, laser fluorescence pen (2190) pooled specificity was 0.77 (95% CI 0.62 to 0.88) for occlusal caries at the dentin detection level; ungraded.
What each review found
Include earlier review versionsNo studies found 0 · 0%GRADE not reported 4 · 100%Very low 0 · 0%Low 0 · 0%Moderate 0 · 0%High 0 · 0%
| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Laser fluorescence pen (DIAGNOdent 2190/Pen) vs Histological validation (serial sectioning, grinding, hemisection, or microradiography) Diagnostic accuracy for occlusal caries detection at the dentin caries detection level (D0-2 versus D3-4) · Extracted human permanent posterior teeth (premolars and molars), occlusal (pit-and-fissure) surfaces · in vitro In in vitro, laser fluorescence pen (2190) pooled specificity was 0.77 (95% CI 0.62 to 0.88) for occlusal caries at the dentin detection level; ungraded. Systematic review and meta-analysis of diagnostic methods for occlusal surface caries. (2021) All outcomes | Specificity 0.77 [0.62, 0.88] | 4 studies | GRADE not reported |
Laser fluorescence pen (DIAGNOdent 2190/Pen) vs Histological validation (serial sectioning, grinding, hemisection, or microradiography) Diagnostic accuracy for occlusal caries detection at the dentin caries detection level (D0-2 versus D3-4) · Extracted human permanent posterior teeth (premolars and molars), occlusal (pit-and-fissure) surfaces · in vitro In in vitro, laser fluorescence pen (2190) pooled sensitivity was 0.63 (95% CI 0.37 to 0.83) for occlusal caries at the dentin detection level; ungraded. Systematic review and meta-analysis of diagnostic methods for occlusal surface caries. (2021) All outcomes | Sensitivity 0.63 [0.37, 0.83] | 4 studies | GRADE not reported |
Laser fluorescence pen (DIAGNOdent 2190/Pen) vs Histological validation (serial sectioning, grinding, hemisection, or microradiography) Diagnostic accuracy for occlusal caries detection at the dentin caries detection level (D0-2 versus D3-4) · Extracted human permanent posterior teeth (premolars and molars), occlusal (pit-and-fissure) surfaces · in vitro In in vitro, laser fluorescence pen (2190) pooled diagnostic odds ratio was 5.85 (95% CI 1.77 to 19.30) for occlusal caries at the dentin detection level; ungraded. Systematic review and meta-analysis of diagnostic methods for occlusal surface caries. (2021) All outcomes | DOR 5.85 [1.77, 19.30] | 4 studies | GRADE not reported |
Laser fluorescence pen (DIAGNOdent 2190/Pen) vs Histological validation (serial sectioning, grinding, hemisection, or microradiography) Diagnostic accuracy for occlusal caries detection at the dentin caries detection level (D0-2 versus D3-4) · Extracted human permanent posterior teeth (premolars and molars), occlusal (pit-and-fissure) surfaces · in vitro In in vitro, laser fluorescence pen (2190) pooled summary ROC AUC was 0.78 for occlusal caries at the dentin detection level; ungraded. Systematic review and meta-analysis of diagnostic methods for occlusal surface caries. (2021) All outcomes | AUC 0.78 | 4 studies | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Systematic review and meta-analysis of diagnostic methods for occlusal surface caries. 2021 All outcomes | 31 December 2018 | 73 | 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.