Maxillary Sinus Augmentation Using Prehydrated Corticocancellous Porcine Bone: Hystomorphometric Evaluation after 6 Months
Bibliographic record
Abstract
BACKGROUND: Insufficient alveolar bone height often prevents the placement of standard dental implants in the posterior part of edentulous maxilla. In order to increase adequately the vertical dimension of the reabsorbed alveolar process, a sinus lift procedure is often necessary. The aim of this study was to evaluate histologic results of a prehydrated corticocancellous porcine bone used in maxillary sinus augmentation. METHODS: Patients (age 18-70 years) with a residual bone height requiring a maxillary sinus augmentation procedure to place dental implants were eligible for this study. All patients were treated with the same surgical technique consisting of sinus floor augmentation via a lateral approach. The space obtained by elevation of the mucosa wall was grafted with prehydrated and collagenated corticocancellous porcine bone. Biopsies were harvested 6 months after the augmentation procedures. RESULTS: Twenty-four patients were enrolled. The mean percentage of new formed bone was 43.9 ± 18.6% (range 7.5-100%), whereas the mean percentage of residual graft material was 14.2 ± 13.6% (range 0-41.9%). The new bone/residual graft material ratio in the maxillary sinuses was 3.1. The mean soft tissues percentage was 41.8 ± 22.7% (range 0-92.5%). CONCLUSION: The present study suggested that porcine bone showed excellent osteoconductive properties and could be used successfully for sinus augmentation. Moreover, the porcine bone showed a high percentage of reabsorption after 6 months; this might be because of the presence of collagen and the porosity of the graft material.
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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".