INVESTIGATING THE ROLE OF ORAL MICROBIOME DYSBIOSIS IN THE DEVELOPMENT AND PROGRESSION OF ATHEROSCLEROSIS AND CARDIOVASCULAR DISEASES: A META-ANALYSIS
Bibliographic record
Abstract
Background: The oral microbiome, comprising bacteria, fungi, and viruses, plays a critical role in oral and systemic health. Disruption of this microbiota balance, termed oral microbiome dysbiosis, is associated with systemic conditions such as cardiovascular diseases (CVDs) and atherosclerosis. Dysbiosis triggers systemic inflammation characterized by elevated pro-inflammatory cytokines and acute-phase proteins, which may exacerbate CVD progression. Despite substantial evidence linking oral dysbiosis to systemic health, the exact extent and mechanisms of this relationship remain underexplored. Objective: This meta-analysis aimed to investigate the association between oral microbiome dysbiosis and cardiovascular diseases, with a particular focus on its role in systemic inflammation and the progression of atherosclerosis. Methods: A systematic search of PubMed, Scopus, and Google Scholar was conducted according to PRISMA guidelines. The analysis included randomized controlled trials, observational studies, and reviews evaluating oral microbiome dysbiosis and its impact on systemic inflammation and cardiovascular outcomes. Data were synthesized using a random-effects model to calculate pooled odds ratios (ORs) and relative risks (RRs) with 95% confidence intervals (CIs). Heterogeneity was assessed using the I² statistic. Subgroup analyses were performed for high-risk populations, including diabetic individuals and patients with periodontitis. Results: Nine studies involving 1,930 participants were included. Pooled analysis revealed significant associations between oral microbiome dysbiosis and systemic inflammation (OR: 1.8; 95% CI: 1.5–2.1; p < 0.01; I² = 30%) and myocardial infarction (RR: 1.4; 95% CI: 1.2–1.6; p = 0.02; I² = 20%). Periodontitis strongly correlated with systemic inflammation (OR: 2.1; 95% CI: 1.8–2.4; p = 0.005; I² = 40%). Subgroup analyses highlighted increased cardiovascular risks in diabetic patients (RR: 1.6; 95% CI: 1.3–1.9) and alcohol drinkers (OR: 1.4; 95% CI: 1.2–1.6). Conclusion: Oral microbiome dysbiosis significantly contributes to systemic inflammation and cardiovascular diseases. Addressing this dysbiosis through interdisciplinary strategies, including oral health interventions and lifestyle modifications, may mitigate cardiovascular risks. Further longitudinal and interventional studies are needed to establish causal pathways and assess the efficacy of periodontal treatments in reducing systemic inflammation.
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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 | 0.020 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.075 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".