Sinus Floor Elevation With Platelet‐Rich Fibrin From Horizontal Centrifugation and Xenograft: Randomized Clinical Trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of maxillary sinus augmentation (MSA) using deproteinized bovine bone material (DBBM) combined with or without platelet-rich fibrin obtained by horizontal centrifugation (H-PRF) after a short healing period of 4 months. MATERIALS AND METHODS: Thirteen patients underwent bilateral two-stage MSA using a split-mouth model. Each side was randomly assigned to receive DBBM alone (control group) or DBBM + H-PRF (test group). Bone tissue samples were harvested 4 months after implant placement and evaluated using microcomputed tomography (micro-CT), as well as histological and histomorphometric analyses. Data were statistically analyzed using paired t-tests (Wilcoxon signed-rank test; p < 0.05). RESULTS: Histomorphometric analysis demonstrated higher amounts (p < 0.05) of newly formed bone in the DBBM + H-PRF group compared to the control group (51.33% ± 6.17% versus 45.68% ± 6.65%, respectively). Micro-CT also revealed significantly higher bone volume (30.38% ± 11.24% and 21.38% ± 9.83%, respectively) and connectivity density (4485 ± 1469 and 2562 ± 1271, respectively) in the DBBM + H-PRF group than in the DBBM-alone group (p < 0.05). CONCLUSIONS: Compared with DBBM alone, maxillary sinuses augmented with H-PRF combined with DBBM exhibited improved qualitative and quantitative new bone formation after 4 months of healing. However, the effects on the long-term survival and early stability of dental implants remain unknown and warrant further investigation with long-term follow-up.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".