Effects of Implant Design and Surface on Bone Regeneration and Implant Stability: An Experimental Study in the Dog Mandible
Bibliographic record
Abstract
BACKGROUND: Previous experimental studies have shown a higher degree of bone-implant contact for surface-enlarged implants compared with machined implants. Yet, there is insufficient evidence that such implants show higher stability and an increased survival rate. PURPOSE: The purpose of this investigation was to study the integration and stability of grit-blasted implants with retention elements on the implant neck, with and without marginal bone defects, compared with machined implants without retention elements. MATERIALS AND METHODS: After tooth extraction of the mandibular premolars in six dogs, two grit-blasted, partly microthreaded Astra Tech implants and one standard Brånemark implant were bilaterally placed in each dog. On one side, 3 x 3 mm large buccal defects were created, to expose three to four implant threads. The contralateral side served as control, and no defects were made. The animals were sacrificed after 4 months of healing. Implant stability was measured using resonance frequency analysis at implant installation and after 4 months of healing. Histologic and histomorphometric evaluation was made after 4 months of healing. RESULTS: Resonance frequency analysis indicated that all implants in the test and control groups were osseointegrated after 4 months, with a tendency toward higher implant stability for the Astra Tech implants. There was a statistically significant higher increase in resonance frequency for the Astra test implants compared with their corresponding controls. Histology and histomorphometry showed well-integrated implants with varying degrees of bone repair at the defect sites. The greater bone-implant contact for the Astra implants was statistically significant. No significant difference between the implants in amount of bone filling the threads was recorded. CONCLUSIONS: The Astra Tech implants tested showed a higher degree of bone-implant contact and higher level of bone regenerated at defect sites compared with the Brånemark implants. Resonance frequency analysis demonstrated a significantly higher increase in the Astra test implants compared with their control groups than did the Brånemark test implants versus their controls.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".