Effect of the buccal gap width following immediate implant placement on the buccal bone wall: A retrospective cone‐beam computed tomography analysis
Bibliographic record
Abstract
BACKGROUND: The effect of the buccal gap width on the clinical outcome of socket graft and immediate implant placement (IIP) at maxillary central incisor sites has not been investigated. Thus, the aim of the present study was to evaluate the effect of the width of the buccal gap on the thickness of the newly formed buccal wall. METHODS: Forty-two patients and 51 maxillary central incisor sites treated with IIP and ridge preservation by means of graft of the buccal gap at the maxillary central incisor region were included in the study. The width of the buccal gap was measured and filled with deproteinized bovine bone mineral. Implant sites were divided into two groups: wide gap (WG, >2 mm; n = 34) and narrow gap (NG, ≤2 mm; n = 17). After at least 1 year in function (5 ± 4), CBCT scans were obtained and assessed by a calibrated examiner. The thickness of the buccal and palatal bone walls, the percentage of the implant height covered by bone in the buccal and palatal aspects and the position of the buccal and palatal crests were compared between the two groups. A linear regression model was performed to assess predictors of the thickness of the buccal bone. RESULTS: The buccal bone was significantly thicker in the WG group than the NG group at all levels observed (overall 1.9 ± 0.9 mm and 0.5 ± 0.6 mm, respectively). The thickness of the palatal bone was similar between both groups (>2 mm). The percentage of the implant height covered by bone at the buccal aspect was significantly higher in the WG group (95 ± 16.6%) than in the NG group (59.4 ± 42.3%). The position of the buccal crest in relation to the implant shoulder was significantly more coronal (0.3 ± 2.2 mm) in the WG group than in the NG group (-4.7 ± 5.6 mm). The regression analysis model indicated that the width of the buccal gap was the only predictor of the thickness of the newly formed buccal bone wall (p < 0.001). CONCLUSION: Grafting of >2 mm-wide buccal gaps following IIP promoted a thicker buccal bone wall.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".