Cancellous Bone Block Allografts for the Augmentation of the Anterior Atrophic Maxilla
Bibliographic record
Abstract
BACKGROUND: Pre-implant augmentative surgery is a prerequisite in many cases in the anterior maxilla to achieve a stable, long-term esthetic final result. PURPOSE: The aim of the present study was to evaluate the outcome of ridge augmentation with cancellous freeze-dried block bone allografts in the anterior atrophic maxilla followed by placement of dental implants. MATERIALS AND METHODS: Thirty-one consecutive patients were included in the study. A bony deficiency of at least 3 mm horizontally and up to 3 mm vertically according to computerized tomography (CT) served as inclusion criteria. Sixty-three implants were inserted after a healing period of 6 months. Nineteen of sixty-three implants were immediately restored. Bone measurements were taken prior to bone augmentation, during implant placement, and at second-stage surgery. RESULTS: Forty-six cancellous allogeneic bone blocks were used. The mean follow-up was 34 ± 16 months. Mean bone gain was 5 ± 0.5 mm horizontally, and 2 ± 0.5 mm vertically. Mean buccal bone resorption was 0.5 ± 0.5 mm at implant placement, and 0.2 ± 0.2 mm at second-stage surgery. Mean bone thickness buccal to the implant neck was 2.5 ± 0.5 mm at implant placement, and 2.3 ± 0.2 mm at second-stage surgery. There was no evidence of vertical bone loss between implant placement and second-stage surgery. Block and implant survival rates were 95.6 and 98%, respectively. All patients received a fixed implant-supported prosthesis. CONCLUSION: Cancellous block allografts appear to hold promise for grafting the anterior atrophic maxilla.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".