Clinical and Histomorphometric Evaluation of Fresh Frozen Bone Allograft in Sinus Lift Surgery
Bibliographic record
Abstract
PURPOSE: The aim of this prospective clinical study was to evaluate the clinical and histomorphometric data of newly formed bone tissue from fresh frozen human allograft in sinus lift surgery. PATIENTS AND METHODS: Thirty-three sinus lift procedures were performed in 20 patients, divided into two groups. The control group (n = 8) received autogenous bone from the mandibular ramus, and the experimental group (n = 12) received fresh frozen bone (FFB) allograft in chips. After 6 months, 52 implants were placed and 50 biopsies were collected for histomorphometric analysis. Cone beam computed tomography scans were performed at preoperative, immediate postoperative, and delayed postoperative time intervals to assess the degree of graft volume loss. RESULTS: There was no statistically significant difference between groups as regards degree of graft volume loss (p = .983), total bone area (p = .191), remaining particles (p = .348), and proportion of active osteoblasts (p = .867). There was a statistically significant difference in the vitality rate between the groups (p = .043). In both groups, all implants were clinically osseointegrated after 4 months. CONCLUSION: FFB allograft was shown to be a feasible substitute for autogenous bone graft in sinus lift surgery.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".