The association between periodontal disease parameters and severity of atherosclerosis
Bibliographic record
Abstract
BACKGROUND: Atherosclerosis is the most common cause for heart attack and stroke. In the last decade, several epidemiological studies have found an association between periodontal infection and atherosclerosis. The aim of this research was to determine the possible association between chronic periodontal disease and severity of atherosclerosis. MATERIALS AND METHODS: Eighty-two subjects that were referred to Chamran Heart Hospital in Isfahan for angiography were involved in this study. Fifty-nine subjects had coronary artery obstruction (CAO) and 23 showed no obstruction after angiography. The severity of CAO was assessed. Periodontal parameters including pocket depth (PD), gingival recession (R), clinical attachment level (CAL), and bleeding on probing (BOP) of all subjects were recorded. The decayed-missing-filled (DMF) index of all subjects was also measured. For statistical analysis, Pearson correlation test, Chi-square, and independent t-test were used. RESULTS: There were significant positive correlation between variables R, PD, CAL, decayed (D), missing (M), DMF, BOP, and degree of CAO. However, there were no significant differences between filling variable degree of CAO (left anterior descending, left circumflex, and right coronary artery). Independent t-test showed that the mean of variables R, PD, AL, D, M, and DMF in patients with obstructed arteries were significantly higher than subjects without CAO. But there were no significant differences between variable F in two groups. CONCLUSION: The results of this cross-section analytical study showed an association between periodontal disease and dental parameters with the severity of CAO measured by angiography. However, this association must not interpret as a cause and effect relationship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".