Horizontal ridge augmentation with particulate cortico‐cancellous freeze‐dried bone allograft alone or combined with injectable‐platelet rich fibrin in a randomized clinical trial
Bibliographic record
Abstract
OBJECTIVES: The objective of this study is to assess the effectiveness of horizontal ridge augmentation using FDBA in combination with injectable-platelet rich fibrin (i-PRF) versus FDBA alone. To fulfill this aim, the radiographic and histomorphometric outcomes are compared. METHOD: The study involved 41 patients who had horizontal alveolar ridge defects categorized as either B (2.5-7 mm) or C (0-2.5 mm). The control group received FDBA alone (n = 20), while the test group received FDBA in combination with i-PRF (n = 21). The horizontal dimensions of the alveolar ridge were measured at 0, 2, 4, and 6 mm from the bone crest using CBCT before and 6 months after alveolar ridge augmentation. In the second-stage surgery, 24 biopsies were taken from the augmented bone - 13 from the control group and 11 from the test group, and were examined histologically and histomorphometrically. The data were analyzed using Pearson correlation coefficient, chi-square, paired-t, and two-sample t tests. RESULTS: There was no significant difference (p > 0.05) in the increase of mean ridge width between the test group and the control group after 6 months at distances of 0, 2, 4, and 6 mm from the crest, with differences of -0.28, 0.12, 0.52, and 1.04 mm, respectively. However, the amount of newly formed bone and material residues was significantly higher in the FDBA + i-PRF group compared to the FDBA alone group (45.01% and 13.06% vs 54.03% and 8.48%, respectively). There was no significant difference in the amount of soft tissue between the two groups (41.02% and 37.5%, p > 0.05). CONCLUSION: The study found that there was no statistically significant difference in the increase of horizontal ridge width between the FDBA + i-PRF group and the FDBA group. However, the histomorphometric analysis revealed that the FDBA + i-PRF group had a higher proportion of newly formed bone, less connective tissue, and fewer residual particles. This suggests a superior quality of bone formation compared to the FDBA group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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".