Assessment of periodontal conditions and systemic disease in older subjects
Bibliographic record
Abstract
BACKGROUND: Panoramic radiographs (PMX)s may provide information about systemic health conditions. AIMS: i). To study clinical periodontal conditions and collect self-reported health status in a cohort of 1084 older subjects; ii). to study signs of alveolar bone loss and carotid calcification from panoramic radiographs obtained from these subjects; and iii). to study associations between study parameters. MATERIAL AND METHODS: PMXs from 1064 adults aged 60-75 (mean age 67.6, SD +/- 4.7) were studied. Signs of alveolar bone loss, vertical defects, and molar furcation radiolucencies defined periodontal status. Medical health histories were obtained via self-reports. Signs of carotid calcification were identified from panoramic radiographs. RESULTS: The PMX allowed assessment of 53% of the films (Seattle 64.5% and Vancouver 48.4%). A self-reported history of a stroke was reported by 8.1% of men in Seattle and 2.9% of men in Vancouver (P < 0.01). Heart attacks were reported by 12% of men in Seattle and 7.2% in Vancouver (N.S.). PMX evidence of periodontitis was found in 48.5% of the subjects, with carotid calcification in 18.6%. The intraclass correlation score for PMX findings of carotid calcification and stroke was 0.24 (95% CI: 0.10-0.35, P < 0.001). The odds ratio for PMX carotid calcification and periodontitis was 2.1 (95% CI: 1.3-3.2, P < 0.001), and for PMX carotid calcification and stroke 4.2 (95% CI: 1.9-9.1, P < 0.001). The associations disappeared when smoking was accounted for. A history of a heart attack was associated with stroke, gender, age, and PMX scores of alveolar bone loss. CONCLUSIONS: PMXs may provide valuable information about both oral conditions and signs of carotid calcification, data that are consistent with self-reported health conditions. Alveolar bone loss as assessed from PMXs is associated with cardiovascular diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".