SynthesisBMC oral health2026
Diagnostic, predictive, and therapeutic approaches for impacted canines: a systematic review and meta-analysis.
Synthesis in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
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Authors and funding
4 authors.
Funding
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Abstract
objectiveMaxillary canine impaction affects approximately 1-3% of the population and presents diagnostic, prognostic, and therapeutic challenges. The clinical utility of artificial intelligence (AI) in this context remains uncertain. We synthesized evidence on diagnostic, predictive, and therapeutic approaches and situated AI-based methods alongside established strategies.
methodsPRISMA 2020-guided searches of PubMed, the Cochrane Library, Web of Science, and Embase (2015-2024) identified 28 eligible studies, grouped into diagnostic, predictive, and therapeutic domains. Risk of bias was assessed using domain-appropriate instruments. Meta-analyses were conducted by domain (no cross-domain pooled effect); diagnostic accuracy synthesis used hierarchical bivariate/HSROC models to accommodate threshold variability.
resultsDiagnostic performance was moderate-to-substantial. CBCT was associated with higher diagnostic accuracy than two-dimensional panoramic radiography (OR 3.13, 95% CI 2.34-4.94; I² = 0.0%, p = 0.121). AI-related diagnostic estimates were reported as higher in a small subset of studies; however, limited sample sizes, heterogeneity, scarce external validation, and inconsistent reporting preclude clinical inference and warrant cautious interpretation. Predictive findings highlighted spatial parameters, particularly inter-tooth/inter-root contact distance. Therapeutic evidence suggested potential benefit of active interceptive interventions over conservative management, but most studies were short-term, heterogeneous, and predominantly non-randomized.
conclusionsCBCT and reproducible spatial indicators provide a practical framework, with imaging guided by radiation protection principles (ALARA). Current evidence does not support AI-based methods as clinically decisive; at best, they may serve as adjunctive, hypothesis-generating tools. Larger prospective studies with longer follow-up, standardized reporting, and rigorous external validation and calibration are needed. CLINICAL
trial registrationPROSPERO Registration Number: CRD420251239971.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.