Associations between dental caries and systemic diseases: a scoping review
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to evaluate and present evidence from animal and human clinical studies on associations between dental caries and systemic diseases, and to suggest potential mechanisms that might explain such associations. METHODS: An electronic search was conducted of PubMed, Embase and Cochrane Central Register of Controlled Trials for articles published from 2010 to 2020 in the English language. From the initial search, 404 full-text studies were assessed for eligibility. After excluding studies for technical and study limitations, a total of 67 studies were included in the summary tables and additional studies were included in the review to support evidence. RESULTS: Few systemic disease and conditions were found to be clinically meaningfully associated with caries experience. Best evidence from human and animal studies described association between metabolic diseases and dental caries. Several interesting animal studies were noted that could generate clinical hypotheses and further investigations in rodent models for cardiovascular injury and hyperglycemia. Inadequate data was found to suggest any modifications to current clinical practice or prevention guidelines. CONCLUSIONS: Limited clinical evidence was found connecting several systemic diseases and dental caries. Inadequate data was found to suggest any modifications to current clinical practice or prevention guidelines. CLINICAL SIGNIFICANCE: Understanding of associations between dental caries and systemic diseases play a crucial role in the treatment planning and education of the dental patient.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".