Clinical Outcomes of an Osteotome Technique and Simultaneous Placement of Neoss Implants in the Posterior Maxilla
Bibliographic record
Abstract
BACKGROUND: Insufficient bone volume often hamper placement of dental implants in the posterior maxilla. PURPOSE: The aim of the present clinical study was to evaluate retrospectively the clinical outcome of implant placement in the resorbed posterior maxilla using an osteotome technique without adding any grafting material. MATERIALS AND METHODS: Twenty patients with 5 to 9 mm of residual alveolar bone height in the posterior maxilla received twenty-nine implants (Neoss Ltd., Harrogate, UK) using an osteotomy technique without bone grafts. Intraoral radiographs were taken before and after implant placement, at the time of loading and after 11 to 32 months of loading (mean 16.4 months), to evaluate bone formation below the sinus membrane and marginal bone loss. Implant stability measurements (Osstell(TM) , Gothenburg, Sweden) were performed after implant installation and at abutment connection 5 months later. All implants were installed with the prosthetic platform level with the bone crest. RESULTS: No implant was lost giving a survival rate of 100% after a mean follow-up time of 16.4 months. The average vertical bone height was 7.2 ± 1.5 mm at placement and 10.0 ± 1.0 mm after 11 to 32 months. The average increase of 2.8 ± 1.1 mm was statistically significant. There was a statistically significant improvement in implant stability from 70.7 ± 9.2 implant stability quotient (ISQ) at placement to 76.7 ± 5.7 ISQ at abutment connection, 5 months later. The mean marginal bone loss amounted to 0.7 ± 0.3 mm after 11 to 32 months of loading. CONCLUSION: It is concluded that the osteotome technique evaluated resulted in predictable intrasinus bone formation, firm implant stability, and good clinical outcomes as no implants were lost and minimal marginal bone loss was observed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".