Dimensional changes after horizontal and vertical guided bone regeneration without membrane fixation using the retentive flap technique: A 1‐year retrospective study
Bibliographic record
Abstract
AIM: To evaluate the dimensional changes after horizontal and vertical guided bone regeneration (GBR) without membrane fixation using the retentive flap technique. METHODS: This study retrospectively examined two cohorts that received vertical or horizontal ridge augmentations (VA or HA groups). GBR was performed using particulate bone substitutes and resorbable collagen membranes. The augmented sites were stabilized using the retentive flap technique without any additional membrane fixation. The augmented tissue dimensions were assessed using cone-beam computed tomography at preoperative, immediately postoperative (IP), 4 months (4M), and 1 year (1Y). RESULTS: Postoperative vertical bone gain in 11 participants of VA group amounted to 5.96 ± 1.88 mm at IP, which decreased to 5.53 ± 1.62 at 4M and to 5.26 ± 1.52 mm at 1Y (intragroup p < 0.05). The horizontal bone gain at IP in 12 participants amounted to 3.98 ± 2.06 mm, which decreased to 3.02 ± 2.06 at 4M and to 2.48 ± 2.09 mm at 1Y (intragroup p < 0.05). The mean implant dehiscence defect height after 1Y was 0.19 ± 0.50 mm in the VA group, and 0.57 ± 0.93 mm in the HA group. CONCLUSION: GBR without membrane fixation using the retentive flap technique seems to preserve the radiographic bone dimensions of vertically augmented sites. This technique may be less effective at preserving the width of the augmented tissue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".