Assessment of periodontal conditions and systemic disease in older subjects
Bibliographic record
Abstract
BACKGROUND: An increased risk for periodontitis has been associated both with type-1 or insulin dependent diabetes (IDDM) and with type-2 or non-insulin dependent diabetes (NIDDM). AIMS: 1) To describe and analyze periodontal conditions in older low-income ethnic diverse subjects with or without a diagnosis of diabetes. 2) To assess to what extent diabetes mellitus is associated with periodontal status, and 3) how periodontitis ranks as a coexisting disease among other diseases in subjects with diabetes mellitus. MATERIAL AND METHODS: Radiographic signs of alveolar bone loss were studied in 1101 older subjects 60-75 years old (mean age 67.6, SD+/-4.7). The number of periodontal sites and the proportions of teeth with probing depth (PD) > or =5 mm, clinical attachment levels (CAL) > or =4 mm were studied in a subset of 701 of the subjects. RESULTS: IDDM was reported by 2.9% and NIDDM by 9.2% of the subjects. The number of remaining teeth did not differ by diabetic status. The number of sites with PD > or =5 mm and the proportion of PD with > or =5 mm was significantly smaller in the non-diabetic group (chi2=46.8, p<0.01, and chi2=171.1, p<0.001, respectively). Statistical analysis failed to demonstrate group differences for the number and proportions of sites with CAL > or =4 mm and for radiographic findings of alveolar bone loss. Combining all periodontal parameters revealed that the Mantel-Haenszel common odds of having IDDM/NIDDM and periodontitis was 1.8 : 1 (95% CI: 1.1-3.1, p<0.03). The common odds ratio estimate of an association between heart disease and diabetes was 3.6 : 1 (95% CI: 2.1-2.6, p<0.001). CONCLUSIONS: Probing depth differences between IDDM/NIDDM vs. non-diabetic subjects may reflect the presences of pseudo-pockets and not progressive periodontitis in many subjects with diabetes mellitus. Periodontitis is not a predominant coexisting disease in older subjects with diabetes mellitus.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".