Alveolar Bone Regeneration for Immediate Implant Placement Using an Injectable Bone Substitute: An Experimental Study in Dogs
Bibliographic record
Abstract
Background: The aim of the present study was to assess the efficacy of a ready‐to‐use injectable bone substitute for bone regeneration around dental implants placed into fresh extraction sockets. Methods: Third and fourth mandibular premolars were extracted from three beagle dogs and the interradicular septa were surgically reduced to induce a mesial bone defect. Thereafter, titanium implants were immediately placed. On the left side of the jaw, mesial bone defects were filled with an injectable bone substitute (IBS), obtained by combining a polymer and biphasic calcium phosphate ceramic granules. The right defects were left unfilled as controls. After 3 months of healing, specimens were prepared for histological and histomorphometric evaluations. Results: No post‐surgical complications were observed during the healing period. In all experimental conditions, histological observations revealed a lamellar bone formation in contact with the implant. Histomorphometric analysis showed that IBS triggers a significant (P <0.05) increase in terms of the number of threads in contact with bone, bone‐to‐implant contact, and peri‐implant bone density of approximately 8.6%, 11.0%, and 14.7%, respectively. In addition, no significant difference was observed when number of threads, bone‐to‐implant contact, and bone density in the filled defects were compared to the no‐defect sites. Conclusion: It is concluded that an injectable bone substitute composed of a polymeric carrier and calcium phosphate significantly increases bone regeneration around immediately placed implants. J Periodontol 2004;75:663‐671.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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 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".