Maxillary vertical alveolar ridge augmentation using sandwich osteotomy technique with simultaneous versus delayed implant placement: A proof of principle randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: The sandwich osteotomy technique usually requires high surgical skills and prolonged intraoperative time and had some technical drawbacks with a subsequent deficient amount of vertical bone gain. The aim of this study was to evaluate the final vertical bone gain using sandwich osteotomy with simultaneous versus delayed implant placement in the anterior maxilla. MATERIAL AND METHODS: This study included 16 patients having multiple missing maxillary anterior teeth with a vertically deficient alveolar ridge. Patients were randomly assigned into two equal groups. Both groups were treated using sandwich osteotomy with interpositional particulate bovine bone graft. In the study group (8 patients, 17 implants), the transport mobilized bone segment was fixed in position using simultaneous implant placement. Whereas in the control group (8 patients, 18 implants), micro-plates and screws were used, followed by a second-stage surgery for plates removal and delayed implant placement. Radiographic assessment included 4 months postoperative mean of vertical gain in alveolar ridge height, taken from cross-sectional cuts of cone beam CT. RESULTS: The mean vertical bone gain in the study group was 4.04 ± 0.59 mm compared to 3.86 ± 0.52 mm in the control group with no statistically significant difference (p = 0.518). The mean value of bone gain percentage in the study group was 33.02% compared to 31.75% in the control group, with no statistically significant difference (p = 0.656). CONCLUSION: The sandwich osteotomy technique with simultaneous implant placement is a reliable method for vertical ridge augmentation that eliminates the need for a secondary surgery.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".