Mandibular Tori as Bone Grafts: An Alternative Treatment for Periodontal Osseous Defects — Clinical, Radiographic and Histologic Morphology Evaluation
Bibliographic record
Abstract
OBJECTIVES: The present study was designed to evaluate the clinical, radiographic and histochemical significance of using the mandibular tori as autogenous bone graft for treatment of intraosseous defects in patients with chronic periodontitis. MATERIALS AND METHODS: Twenty-eight sites from 14 patients with chronic periodontitis were included in this study. Each patient was treated with split mouth design; one site received torus mandibularis bone graft and the other site received a full-thickness fap alone. Histopathologic assessment was evaluated on removal of torus mandibularis to evaluate its histologic structure and by the end of the study 9 month later. Clinical and radiographic parameters were re-evaluated at 3 months interval for 1 year. RESULTS: The results of the present study revealed significant gain in the clinical attachment level (CAL) (88.4%, 4.53 ± 0.06 mm) for torus mandibularis sites compared to (39.7%, 2.01 ± 0.04 mm) for full-thickness fap. Moreover, there was a reduction in the probing pocket depth (PPD) of (75.4%, 5.75 ± 0.12 mm) for torus mandibularis sites and (49.6%, 3.73 ± 0.14 mm) for sites treated with a full-thickness fap only; CAL and PPD differences were significant at p-value ≤0.01. Concomitantly, significant radiographic increase in the bone height and density were recorded in the test group. CONCLUSION: The use of mandibular tori as autogenous bone graft could provide benefits as a periodontal therapeutic modality and enhance regenerative potential of periodontal intraosseous defects.
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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 | 0.000 | 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".