Does tooth brushing protect from atrial fibrillation and heart failure?
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia in the general population, and it is associated with an increased risk of stroke, congestive heart failure (CHF), death, and cognitive dysfunction.1,,–4 CHF is a frequent cause of hospital admission and death.5,–7 Both disorders often occur together, have similar underlying risk factors, and their combination strongly correlates with increased morbidity and mortality.8,–10 Common risk factors include older age, elevated blood pressure, coronary artery disease, valvular heart disease, and diabetes mellitus.11,–13 Inflammation has also been associated with both AF and CHF.14,–16 Observational and histopathological studies have shown that an increased inflammatory state, mainly measured by inflammatory biomarkers, not only increases the likelihood of AF initiation and progression, but also the risk of developing and worsening CHF.17,–19 Poor oral hygiene is an established risk marker for cardiovascular disease.20 It has been hypothesized that poor oral hygiene may lead to transient bacteremia, which may cause systemic inflammation. However, little information has been available on the relationships of poor oral hygiene with the incidence of AF and CHF.
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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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.021 | 0.019 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".