In‐Situ vs. Ex‐Situ Bone Onlay Grafting for Horizontal Ridge Augmentation of Anterior Teeth: A Retrospective Study
Bibliographic record
Abstract
OBJECTIVES: This study aimed to systematically compare the efficacy and resorption of in-situ and ex-situ bone onlay grafting in reconstructing horizontal alveolar ridge defects of anterior teeth. METHODS: One-hundred and twenty five patients receiving autogenous bone onlay grafts in the anterior tooth region were included in this study, which comprised 55 patients with 66 implants receiving in-situ bone grafts (in-situ group) and 70 patients with 77 implants receiving ex-situ bone grafts (ex-situ group). All patients were examined by CBCT scanning before bone augmentation (T0), immediately after bone augmentation (T1), at 5-8 months after bone augmentation (T2), immediately after implant placement (T3), and 5-8 months after implant placement (T4). Horizontal bone width (HBW) and bone volume (BV) were measured at different postoperative time points after automated image registration of consecutive CBCT imaging. RESULTS: The resorption rate of HBW from T1 to T2 in the in-situ group (23.84% ± 17.07%) was significantly lower than that in the ex-situ group (38.77% ± 19.94%) (p < 0.0001). However, from T3 to T4, no significant difference was observed between the two groups. Additionally, from T1 to T2, there were significant differences in the resorption rate of BV between the in-situ group (20.03% ± 16.14%) and the ex-situ group (28.20% ± 17.58%) (p < 0.05). In contrast, no significant differences between the two groups from T3 to T4 were noted. CONCLUSIONS: Both in-situ and ex-situ onlay graftings showed a satisfactory outcome in bone augmentation, yet in-situ bone graft had more bone augmentation and better stability than ex-situ bone graft.
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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 | 0.000 | 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".