Histologic and histomorphometric evaluation of an allograft stem cell-based matrix sinus augmentation procedure.
Bibliographic record
Abstract
PURPOSE: Long-term success of dental implants has been demonstrated when placed simultaneously with or after a sinus augmentation procedure. However, optimal bone formation can be from 6 to 9 months or longer with grafting materials other than autogenous bone. For this reason, there is interest in any surgical technique that does not require autogenous bone harvesting, yet results in sufficient bone formation within a relatively short time frame. MATERIALS AND METHODS: This study evaluated and compared bone formation following sinus-augmentation procedures using either an allograft cellular bone matrix (ACBM), containing native mesenchymal stem cells and osteoprogenitors, or conventional allograft (CA). RESULTS: Histomorphometric analysis of the ACBM grafts revealed average vital bone content of 32.5% ± 6.8% to residual graft content of 4.9% ± 2.4% for the 21 sinuses in the study, at an average healing period of 3.7 ± 0.6 months. Results for the CA, in the same time frame, were average vital bone content of 18.3% ± 10.6% to residual graft content of 25.8% ± 13.4%. A comparison of ACBM and CA grafts, for both vital and residual bone contents, showed P values of .003 and .002, respectively, indicating a statistically significant difference between the groups. CONCLUSION: The high percentage of vital bone content, after a relatively short healing phase, may encourage a more rapid initiation of implant placement or restoration when a cellular grafting approach is considered.
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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".