Is There a Causal Link Between Periodontitis and Cardiovascular Disease? A Concise Review of Recent Findings
Bibliographic record
Abstract
There is substantial evidence in support of an association between periodontitis and cardiovascular disease. The most important open question related to this association is causality. This article revisits the question of causality by reviewing intervention studies and systematic reviews and meta analyses published in the last 3 years. Where are we now in answering this question? Whilst systematic reviews and epidemiological studies continue to support an association between the diseases, intervention studies fall short in determining causality. There is a dearth of good-quality, blinded randomised control trials with cardiovascular disease outcomes. Most studies use surrogate markers/biomarkers for endpoints, and this is problematic as they may not be reflective of cardiovascular disease status. This review further highlights another issue with surrogate markers/biomarkers: the potential for collider bias. Ethical considerations surrounding nontreatment have led to calls for a well-annotated database containing in-depth dental health data. Finally, a relatively new and important risk factor for cardiovascular disease, clonal haematopoiesis of indeterminate potential, is discussed. Clonal haematopoiesis of indeterminate potential increases cardiovascular risk by more than 40%, and inflammation is a contributing factor. The impact of periodontal disease on this emerging risk factor has yet to be explored. Although the question of causality in the association between periodontal disease and cardiovascular disease remains unanswered, the importance of good oral health in maintaining good heart health is reiterated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".