Minimal invasive crestal sinus technique using autologous fibrin glue versus sticky bone with simultaneous implant insertion: a prospective study
Bibliographic record
Abstract
Introduction: Following tooth extraction, posterior maxilla frequently experiences bone resorption and maxil lary sinus pneumatization, resulting in resorption of bone with insufficient dimension for adequate dental implants placement.Objectives: This clinical investigation was performed to assess implant stability and radiographic outcomes us ing autologous fibrin glue (AFG) against sticky bone combined with crestal sinus lift procedure and simultaneous implant insertion. Material and methods:The study involved 12 implants in ten patients with residual bone height from 5 to 9 mm, divided into two groups.In group A, AFG was applied for maxillary sinus augmentation, while in group B, sticky bone was used for maxillary sinus augmentation.All patients were followedup clinically to evaluate im plant stability at baseline (T 0 ), third month (T 3 ), and ninth month (T 9 ) as well as radiographically to evaluate residual bone height, implant protrusion, graft apical height, and graft sinus height at same time intervals.Data were analyzed using (IBM SPSS software, version 26.0).Pvalue ≤ 0.05 was considered statistically significant.Results: A total of 10 patients (8 females, 2 males) participated in the study, with mean age ± SD of 29.83 ± 3.54 years in group A, and mean age ± SD of 32 ± 3.89 years in group B. At T 0 , T 3 , and T 9 followup, there was a statistical significance within each group (with p < 0.001 in all studied parameters).However, there were no sig nificant differences between both groups, with p = 0.843, 0.296, and 0.451 regarding implant stability, p = 0.221, 0.244, and 0.276 in graft apical height, and p = 0.435, 0.494, and 0.673 regarding graft sinus height, respectively.Conclusions: AFG can be applied as a noninferior material during sinus lifting with advantages including fewer complications, easy preparation procedure, less timeconsuming, and affordable cost.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".