Evaluation of L‐PRF combined with deproteinized bovine bone mineral for early implant placement after maxillary sinus augmentation: A randomized clinical trial
Bibliographic record
Abstract
PURPOSE: To investigate the effectiveness of adding leukocyte and platelet-rich fibrin (L-PRF) to deproteinized bovine bone mineral (DBBM) for early implant placement after maxillary sinus augmentation. MATERIALS AND METHODS: Twelve patients requiring two-stage bilateral maxillary sinus augmentation were enrolled to the study. The elevated sinus cavities were randomly grafted with DBBM + L-PRF (test) or DBBM alone (control) in a split-mouth design. Implants were placed in the augmented sites after 4 months in the test group and 8 months in the control group. Bone biopsies were collected during implant placement for histomorphometric evaluation. Resonance frequency analysis was performed immediately after implant placement and at implant loading in both groups. Cone-beam computed tomography was obtained preoperatively and postoperatively for evaluation of graft volume changes. RESULTS: Both procedures were effective for maxillary sinus augmentation. Cone-beam computed tomography analysis did not reveal differences in graft volume between test and control group at any of the evaluated time points (P > .05). Histological evaluation demonstrated increased percentage of newly formed bone for the test group (44.58% ± 13.9%) compared to the control group (30.02% ± 8.42%; P = .0087). The amount of residual graft in the control group was significantly higher (13.75% ± 9.99%) than in the test group (3.59 ± 4.22; P = .0111). Implant stability quotient (ISQ) immediately after implant placement was significantly higher in the control group (75.13 ± 5.69) compared to the test group (60.9 ± 9.35; P = .0003). The ISQ values at loading did not differ between the groups (P = .8587). Implant survival rate was 100% for both groups. CONCLUSION: The addition of L-PRF to the DBBM into the maxillary sinus allowed early implant placement (4 months) with increased new bone formation than DBBM alone after 8 months of healing.
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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) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".