Question · asked by 1 review

Digital bitewing radiography, phosphor plate (PSP) 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
Digital bitewing radiography, phosphor plate (PSP)
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, digital bitewing radiography (phosphor plates) pooled specificity was 0.95 (95% CI 0.59 to 0.995) for occlusal caries at the dentin detection level; ungraded.

What each review found

Include earlier review versions
No studies found 0 · 0%GRADE not reported 4 · 100%Very low 0 · 0%Low 0 · 0%Moderate 0 · 0%High 0 · 0%
FindingEffectStudiesGRADE certainty
Digital bitewing radiography (phosphor plates) 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, digital bitewing radiography (phosphor plates) pooled specificity was 0.95 (95% CI 0.59 to 0.995) 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 0.95 [0.59, 0.995]2 studiesGRADE not reported
Digital bitewing radiography (phosphor plates) 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, digital bitewing radiography (phosphor plates) pooled summary ROC AUC was 0.73 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 0.732 studiesGRADE not reported
Digital bitewing radiography (phosphor plates) 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, digital bitewing radiography (phosphor plates) pooled sensitivity was 0.48 (95% CI 0.24 to 0.73) 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 0.48 [0.24, 0.73]2 studiesGRADE not reported
Digital bitewing radiography (phosphor plates) 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, digital bitewing radiography (phosphor plates) pooled diagnostic odds ratio was 15.57 (95% CI 0.47 to 515.27) 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 15.57 [0.47, 515.27]2 studiesGRADE not reported

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

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Systematic review and meta-analysis of diagnostic methods for occlusal surface caries.
2021 All outcomes
31 December 201873Not 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.