Implant Survival Rates after Osteotome‐Mediated Maxillary Sinus Augmentation: A Systematic Review
Bibliographic record
Abstract
PURPOSE: The aim of the present study was to systematically evaluate the implant survival rate after osteotome-mediated maxillary sinus augmentation with or without using grafting materials. MATERIALS AND METHODS: MEDLINE database was searched using a combination of specific search terms. Furthermore, a hand searching of the relevant journals and of the bibliographies of reviews was performed. Prospective and retrospective clinical studies with at least 20 patients treated by osteotome-mediated sinus floor elevation were included. RESULTS: Nineteen studies were selected for data analysis. A total of 1,822 patients, accounting for 3,131 implants were considered. Mean weighted cumulative implant survival at 1, 2, 3, and 5 years was estimated as 98.12%, 97.40%, 96.75%, and 95.81%, respectively. No significant difference was found in relation to the use of grafting material nor in relation to implant length. Overall implant survival was 92.7% for 331 implants placed in <5 mm ridge height and 96.9% for 2,525 implants inserted in ≥ 5 mm ridge height. The difference was significant (p = .0003). CONCLUSIONS: The transalveolar sinus augmentation technique could be a viable treatment in case of localized atrophy in the posterior maxilla even in case of minimal residual bone height. The prognosis can be more favorable when the residual ridge is at least 5 mm high.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".