Implants in Reconstructed Bone: A Comparative Study on the Outcome of Straumann® Tissue Level and Bone Level Implants Placed in Vertically Deficient Alveolar Ridges Treated by Means of Autogenous Onlay Bone Grafts
Bibliographic record
Abstract
PURPOSE: To evaluate: (1) the survival rate of Straumann® Tissue Level and Bone Level implants placed in atrophic edentulous jaws previously reconstructed by means of autogenous onlay bone grafts; (2) to compare peri-implant bone resorption values over time. MATERIALS AND METHODS: From 2005 to 2010, 50 patients presenting with vertical or tridimensional defects of the edentulous ridges were treated with autogenous bone grafts. Three to 7 months afterward, 192 implants were placed (Group A: 97 Tissue Level implants; Group B: 95 Bone Level implants) in the reconstructed areas. After a further waiting period of 2 to 3 months, patients were rehabilitated with implant-supported fixed prostheses. The follow-up ranged from 12 to 68 months after the start of prosthetic loading (mean: 33 months). RESULTS: No implants were removed (survival rate: 100%), but in Group B 13 implants (8 placed in iliac grafts, 2 placed in ramus grafts, and 3 placed in calvarial grafts) presented peri-implant bone resorption values higher than those proposed by Albrektsson and colleagues. for successful implants: the overall implant success rate was then 100% for Group A and 86.8% for Group B. No prosthetic failures were recorded, thus leading to a 100% prostheses success rate. CONCLUSION: No significant differences were found between the two types of implants as far as implant survival rate is concerned, but results from this study seem to demonstrate that Tissue Level implants may present better long-term results in terms of peri-implant bone maintenance, as compared with Bone Level implants, when placed in reconstructed areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".