Evaluation of autogenous tooth graft in regeneration of periodontal vertical alveolar defects: clinical, radiographic, and experimental study
Bibliographic record
Abstract
Introduction: Periodontitis is a chronic inflammatory disease, in which destruction of the periodontium occurs.Not well-treated periodontitis causes teeth loss and problems regarding speech and appearance.Objectives: To evaluate the effectiveness of tooth particles as a graft material in the regeneration of periodontal vertical alveolar defects clinically and regeneration of bone defect experimentally.Material and methods: A total of 21 patients with stage III severe periodontitis, aged 25 to 45 years, having periodontal vertical defects were selected for the study.They were randomly divided into 3 groups, in which splitmouth study design was used.In group 1, right side was treated by open flap debridement (OFD) alone, and left side with autogenous tooth graft particles.In group 2, control side treated by OFD, and left side using beta-tricalcium phosphate (β-TCP) graft material.In group 3, left side was treated using autogenous tooth graft, and right side using β-TCP graft.For the experimental part, a total of 21 rats had an intended surgical bony defect at diastema area, and were randomly divided into 3 groups.In group 1, defects were created without addition of any graft material.In group 2, defects were filled with β-TCP graft material.In group 3, autogenous tooth particles were used.Clinical data, including plaque index (PI), gingival index (GI), periodontal probing depth (PPD), clinical attachment level (CAL), and radiographic parameters were recorded at baseline and 3 and 6 months post-surgically.For the experimental part, animals were sacrificed one month later.Tissue specimens were prepared for histological analysis.Results: After 3 and 6 months post-treatment, there was an improvement in PI and GI in all the groups.Also PPD, CAL gain, and radiographic bone formation were significant for autogenous tooth-grafted sites and β-TCP-grafted sites, with a significant improvement in PPD and CAL for tooth-grafted sites compared with β-TCP-grafted sites.Histologically, the amount of new bone formation was higher in group 3 compared with group 1 and 2. Conclusions: It can be concluded that autogenous tooth particles can be considered as an effective and suitable bone graft material used in the treatment of intra-bony defects in patients with chronic severe periodontitis.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".