Localized Management of Sinus Floor Technique for Implant Placement in Fresh Molar Sockets
Bibliographic record
Abstract
BACKGROUND: The use of osteotome for vertical bone augmentation and localized sinus elevation with minimal surgical trauma represents a suitable procedure to increase the vertical dimension of available bone for implant placement. PURPOSE: The aim of this study was to report clinical and radiographic results of localized management of sinus floor (LMSF) in fresh molar sockets at 13-year follow-up. MATERIALS AND METHODS: Fifty-three patients, needing one or two maxillary molar extraction, were enrolled in this study. LMFS procedure was performed and 68 implants were positioned. A presurgical distance from the alveolar crest to the floor of the maxillary sinus and the amount of new radiopacity between the sinus floor and alveolar crest were measured from the mesial and distal surfaces of each dental implant surface. RESULTS: After a mean follow-up period of 9.76 ± 5.27 years (ranged from 4 to 17 years) a survival rate of 100% was reported. Mean bone height at temporary prosthesis placement was 7.99 ± 1.16 mm. They were stable over time, reporting a mean value of 8.01 ± 1.46 mm at 13-year follow-up. CONCLUSIONS: The results of this study demonstrated that LMSF procedure in fresh molar sockets allowed to expand the dimensions of resorbed posterior maxillary alveolar bone both vertically and horizontally with a success rate of 100% of implant osseointegration over time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".