Maxillary Sinus Floor Augmentation Surgery with Autogenous Bone Grafts as Ceiling: A Pilot Study and Test of Principle
Bibliographic record
Abstract
BACKGROUND: Studies have pointed out that the mere elevation of the maxillary sinus membrane might suffice to allow for bone formation indicating the additional use of augmentation materials to be redundant. PURPOSE: The purpose of this study was to assess whether elevation of the sinus mucosal lining combined with applying an autologous bone graft as a ceiling and placement of a short implant would allow for bone formation around the implant thus surpassing the need for applying augmentation materials around the installed implants. MATERIALS AND METHODS: Fourteen consecutive patients were subjected to maxillary sinus floor elevation surgery and simultaneous placement of an implant. Using the lateral bone-wall window technique, the membrane was exposed and elevated. Next, a bone graft taken from the zygomatic rim was placed as a ceiling above the inserted implant to ensure that the sinus membrane would not collapsed around a significant part of the implant. Finally, the bone window was returned in place. After connecting the healing abutment, the wound was closed. RESULTS: All implants were stable and no implants were lost. There were no complications after harvesting the bone graft. Radiographic evaluation showed a bone gain of 3.2 ± 0.9 mm after 3 months and 3.6 ± 0.9 mm after 1 year. Less than 6% of the implant was not covered by bone after 1 year. CONCLUSION: Maxillary sinus membrane elevation and simultaneous placement of short endosseous implants with a bone graft as a ceiling on top of the implant result in predictable bone formation around the implant and good osseointegration on radiographs.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".