Bioceramics for Guided Bone Regeneration: A Multicenter Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVES: To compare the clinical effectiveness of a novel bioceramic (BC) with a control xenograft (BO) for guided bone regeneration (GBR) performed simultaneously with implant placement. MATERIALS AND METHODS: This clinical study enrolled patients with insufficient bone volume who required GBR during implant placement to increase bone width using either BC or BO. Outcome measures included a dimensional reduction in buccal bone thickness measured by cone beam computed tomography performed immediately post-surgery and at 6 months postoperatively (ΔHBBT), soft tissue healing at 14 days, 1 month, and 6 months postoperatively, and complications rates. The primary outcome was the change in buccal bone thickness around the implant. RESULTS: Of the total 152 patients included, 76 from each group received BC and BO treatments. The ΔHBBT in BC and BO groups were -0.276 mm (-0.432, -0.121) and -0.614 mm (-0.769, -0.459) mm, respectively, rejecting the null hypothesis. No significant difference in soft tissue healing was observed between the two groups, with no inflammatory changes in 96.05% and 90.79% of the BC and BO groups, respectively, at 2 weeks postoperatively. However, the BC group exhibited a lower overall complication rate (3.95%), including mild inflammation, poor soft tissue healing, and bone graft extrusion in 3 out of 76 patients. CONCLUSIONS: Both BC and BO demonstrated favorable outcomes in bone regeneration and soft tissue healing when used for simultaneous implant placement and bone augmentation.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".