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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".