Measurements of Buccal Tissue Volumes at Single‐Implant Restorations after Local Bone Grafting in Maxillas: A 3‐Year Clinical Prospective Study Case Series
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to measure changes in buccal and proximal tissue volumes after local bone grafting and single-implant treatment. MATERIALS AND METHODS: Ten patients were provided with buccal bone grafts 6 months prior to implant treatment in central upper incisor regions. Following a healing time of 6 months, abutments and single-implant crowns were installed and followed up for 2 years. Clinical photographs and impressions were taken prior to the surgical intervention as well as after crown placement and at first and second annual checkups. The photographs and study models were analyzed with regard to papilla regeneration and changes in buccal crest volume during the study period by means of a clinical papilla index and optical scanning of study models. RESULTS: All bone grafts healed without problems. A significant reduction of the buccal crest volume (-50%, p <.01) was observed in the grafted area before abutment connection. However, a significant increase of tissue volume (+100%, p <.05) was noticed at the subsequent crown placement, followed by a second but slow reduction of the volume during the following 2 years of function. The interdental papillae increased significantly (p <.05) in volume during the first year, almost completely filling up the embrasure areas after 2 years. CONCLUSIONS: It may be concluded that local bone grafting seems to be a valuable protocol to create sufficient bone volume for implant placement. However, significant resorption of the graft may be present, which reduces the impact of grafting on the esthetic outcome. Instead, placement of the abutment cylinder and the crown seems to play a more important role for reestablishing the tissue volume at the implant-supported single crowns.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".