Two‐Center Prospective, Randomized, Clinical, and Radiographic Study Comparing Osteotome Sinus Floor Elevation with or without Bone Graft and Simultaneous Implant Placement
Bibliographic record
Abstract
Abstract Purpose To evaluate stability and success rate of hydrophilic nanostructured implants placed via osteotome sinus floor elevation (OSFE) without grafting material or using β‐tricalcium phosphate (β‐TCP), deproteinized bovine bone (DBB), or their combination, and also to assess three‐dimensional volumetric stability of endo‐sinus bone gained in the aforementioned conditions. Materials and Methods OSFE with simultaneous implant placement (10‐mm long SLActive‐BL®, Straumann, Basel, Switzerland) was performed. Grafting materials were randomly allocated to implant sites, whereas one site was left without graft. Implant stability was measured by resonance frequency analysis over 6 months. Implant success was evaluated after 2 years of loading. Volume of new endo‐sinus bone was calculated from CBCT images using 3D Slicer® software. Results A total of 180 implants were inserted into posterior maxilla of 45 patients with 6.59 ± 0.45 mm of residual bone height, and all remained successful after 2 years. Implant stability steadily increased during healing, without significant difference between groups (p = .658). After 2 years, endo‐sinus bone significantly shrank (p < .001) in all groups (DBB:66.34%; β‐TCP:61.44%; new bone formed from coagulum: 53.02%; β‐TCP + DBB:33.47%). Conclusions Endo‐sinus bone gained after OSFE inevitably and significantly shrinks regardless of whether grafting material is applied or not. Grafting material offers no significant advantage to stability nor clinical success of hydrophilic and nanostructured implants placed simultaneously with OSFE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".