A 10‐Year Clinical and Radiographic Study of Implants Placed after Maxillary Sinus Floor Augmentation with an 80:20 Mixture of Deproteinized Bovine Bone and Autogenous Bone
Bibliographic record
Abstract
BACKGROUND: There is a need for prospective, long-term follow-up studies of implants placed after maxillary sinus floor augmentation (MSFA). PURPOSE: The aim of the present study was to determine whether deprotenized bovine bone (DPBB) used for MSFA may result in long-term stability of placed dental implants. MATERIAL AND METHODS: Fourteen of the 20 patients included in the study were followed throughout the 10 years study period. These patients had 53 implants placed in 22 (6 unilateral and 8 bilateral) maxillary sinuses augmented with a mixture of 80% DPBB and 20% autogenous bone (80:20), and 15 implants placed in non-grafted sites. Clinical and radiographic examinations of the implants and grafts were performed. RESULTS: After 10 years of functional loading 15 of the initially placed 108 implants had been lost giving a cumulative survival rate of 86%. The mean marginal bone loss was 1.6 ± 1.0 mm. There were no statistically significant differences in marginal bone level, pocket depth, or ISQ-values between implants placed in residual or grafted bone or between smokers or non-smokers at 10 years follow-up. There was a statistically significant reduction (p < .01) in graft height between 3 months and 2 years but no further significant reduction up to 10 years. CONCLUSIONS: The first 2 years after placement of implants with turned surfaces placed in sites after sinus floor augmentation with DPBB and autogenous bone seem to be critical for implant survival. At 10 years follow-up, the remaining implants presented excellent clinical and radiological results regardless of smoking habits or implant sites (augmented or residual bone).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".