Re‐osseointegration following reconstructive surgical therapy of experimental peri‐implantitis. A pre‐clinical in vivo study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of bone substitute materials on hard and soft tissue healing in reconstructive surgical therapy of experimental peri-implantitis at implants with different surface characteristics. MATERIAL AND METHODS: Six female, Labrador dogs were used. 3 months after tooth extraction, four implants with two different surface characteristics (A and B) were installed on each side of the mandible. Experimental peri-implantitis was induced 3 months later. During surgical treatment of peri-implantitis, the implants were cleaned with curettes and cotton pellets soaked in saline. The implant sites were allocated to one of four treatment categories; (a) Group C; no augmentation, (b) Group T1; bone defect filled with deproteinized bovine bone mineral (c) Group T2; bone defect filled with a biphasic bone graft material, (d) Group T3; bone defect filled as T1 and covered with a collagen membrane. Clinical and radiological examinations were performed, and biopsies were obtained and prepared for histological analysis 6 months after peri-implantitis surgery. RESULTS: Implant B (smooth surface) sites showed significantly (a) larger radiographic bone level gain, (b) enhanced resolution of peri-implantitis lesions, and (c) larger frequency of re-osseointegration than implant A (moderately rough surface) sites. Implant B sites also showed superior preservation of the mucosal margin. Differences between bone substitute materials and control procedures were overall small with limited advantages for T1 and T2 sites. CONCLUSION: Healing following reconstructive surgical treatment of experimental peri-implantitis was superior around implants with a smooth surface than implants with a moderately rough surface. Benefits of using bone substitute materials during surgical therapy were overall small.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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 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".