Periodontal disease, but not edentulism, is independently associated with increased plasma fibrinogen levels
Bibliographic record
Abstract
The systemic response to periodontal disease was analyzed in the cross-sectional Study of Health in Pomerania (SHIP). The completed data of 2,738 subjects aged 20 to 59 years were used for logistic regression analysis with an increased plasma fibrinogen level (> or =3.25 g/L according to Clauss) as the dependent variable. Participants were divided into four groups according to the number of periodontal pockets > or =4 mm (0, 1-7, 8-14, > or =15 pocketing). An additional group comprised the 52 edentulous subjects. The adjusted odds ratio (OR) of > or =15 periodontal pockets for increased plasma fibrinogen levels was 1.88 (95% CI: 1.25-2.83). Edentulism per se was not associated with increased plasma fibrinogen levels but was contained in a two-way interaction with the number of cigarettes/day in current smokers (p = 0.031). For edentulous nonsmokers the adjusted OR was 1.10 (95% CI: 0.51-2.39). Furthermore, body mass index, the interaction between gender and body mass index, serum LDL cholesterol, medication, the interaction between LDL cholesterol and medication, aspirin, smoking, school education, chronic bronchitis, and the interaction between alcohol consumption and chronic gastritis were associated with plasma fibrinogen levels. Our results show that periodontal disease but not edentulism per se is associated with an increased plasma fibrinogen level.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".