Morphometric and histologic characterization of alveolar bone from hypertensive patients
Bibliographic record
Abstract
BACKGROUND: Hypertension is considered a risk factor in implant dentistry but the underlying reasons remain unclear. It may be that hypertension has a negative impact on the local bone quality. PURPOSE: Here we evaluated the structural and histological parameters of bone collected from hypertensive patients treated by antagonists of the renin-angiotensin system, and of bone collected from normotensive patients. MATERIAL AND METHODS: A total of 30 patients were referred for rehabilitation with dental implants to be placed in the posterior mandible. The first group were hypertensive patients treated with RAS antagonists. The second group were normotensive patients not taking medication. Bone biopsies collected during implant installation were subjected to analysis. Micro CT revealed the structural parameters. Histological analyses together with immunohistochemical staining of osteogenic markers were performed. RESULTS: The structural parameters of bone volume, trabecular thickness, trabecular number, separation of the trabecular, and total porosity were similar between the 2 groups (P > .05). The histological appearance of bone derived from hypertensive patients was normal. The staining pattern of Runx-2, osteopontin, and osteocalcin were comparable in both groups. CONCLUSIONS: These observations suggest that hypertensive patients treated with renin-angiotensin system antagonists have regular alveolar bone with respect to bone structure and histological parameters.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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 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".