A retrospective study of an alternative technique for implant repositioning in the maxillary esthetic region
Bibliographic record
Abstract
BACKGROUND: Implant-bone block segment repositioning may be an option of treatment for patients with vertical alveolar bone atrophy. PURPOSE: To assess implant-bone block movement, gingival outcome and the subjective appreciation of patients after an alternative treatment of an implant-bone block segment repositioning in the maxillary esthetic region. MATERIALS AND METHODS: Patients who underwent implant-bone block segment relocation in areas of vertical alveolar bone atrophy in the anterior esthetic region were assessed. The outcome measures were implant failure, complications after initial loading, vertical bone augmentation, papilla index, width of the keratinized mucosa, and patient satisfaction. RESULTS: Twenty-five implants in nine consecutive patients were included in this study. During the follow-up period, only one implant failed. Vertical bone augmentation ranged from 3.0 to 8.4 mm (mean 4.9 mm). A significant improvement (P < .001) in the papilla index was observed, improving the esthetic outcome. Six patients (66.6%) had more than 2 mm of keratinized mucosa and all of the patients were satisfied with the treatment. CONCLUSIONS: The esthetics and functional gingival outcome of oral rehabilitation in areas with vertical alveolar bone atrophy can be successfully improved with the presented technique, which had a high overall implant survival rate within a short period.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".