Effect of periodontal disease on diabetes: systematic review of epidemiologic observational evidence
Bibliographic record
Abstract
BACKGROUND: Periodontal disease and diabetes mellitus are common, chronic diseases worldwide. Epidemiologic and biologic evidence suggest periodontal disease may affect diabetes. OBJECTIVE: To systematically review non-experimental, epidemiologic evidence for effects of periodontal disease on diabetes control, complications and incidence. DATA SOURCES: Electronic bibliographic databases, supplemented by hand searches of recent and future issues of relevant journals. Study eligibility criteria and participants: Longitudinal and cross-sectional epidemiologic, non-interventional studies that permit determination of directionality of observed effects were included. STUDY APPRAISAL AND SYNTHESIS METHODS: Four reviewers evaluated pair-wise each study. Review findings regarding study results and quality were summarized in tables by topic, using the PRISMA Statement for reporting and the Newcastle-Ottawa System for quality assessment, respectively. From 2246 citations identified and available abstracts screened, 114 full-text reports were assessed and 17 included in the review. RESULTS: A small body of evidence supports significant, adverse effects of periodontal disease on glycaemic control, diabetes complications, and development of type 2 (and possibly gestational) diabetes. LIMITATIONS: There were only a limited number of eligible studies, several of which included small sample sizes. Exposure and outcome parameters varied, and the generalizability of their results was limited. CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS: Current evidence suggests that periodontal disease adversely affects diabetes outcomes, and that further longitudinal studies are warranted.
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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 | 0.014 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".