Iliac crest vertical block grafts −placing outside or inside the bone contour: A cohort study
Bibliographic record
Abstract
OBJECTIVE AND AIM: Challenging defect configurations and dimensions arise from severe, localized vertical alveolar ridge defects caused by trauma or prior surgery. This study aims to analyze three-dimensional bone gain, assess marginal bone stability in such defect configurations, and evaluate the impact of grafting outside the bone contour on the overall outcome, with a focus on iliac crest block grafts as a valid treatment option. MATERIALS AND METHODS: The prospective cohort study evaluated patients who required vertical block grafting due to localized bone defects in the maxilla or mandible and who had received iliac grafts. Three-dimensional bone gain was analyzed using cone beam computed tomography (CBCT) after 3 months of bone healing for each treated site and implant position. A comparison between bone grafts inside and outside the bone contour was conducted. Marginal bone stability was measured using intraoral radiographs during routine annual follow-up visits. RESULTS: Seventy patients with 89 treated sites were evaluated. After 3 months of graft healing, the mean vertical bone gain was 11.03 ± 3.54 mm, the mean horizontal bone gain was 7.18 ± 2.00 mm, and the mean graft length was 28.19 ± 11.01 mm. A total of 217 implants were placed in the augmented regions. On implant level, a mean vertical bone gain of 10.44 ± 3.44 mm and a mean horizontal bone gain of 6.54 ± 1.86 mm were measured. Over a 43-month observation period, mesial and distal marginal bone loss averaged 0.44 ± 0.92 mm and 0.49 ± 1.05 mm, respectively. Eight implants were diagnosed with periimplantitis, resulting in the loss of four implants, while no early implant losses were reported. CONCLUSION: Within the limitations of this study, vertical bone grafts with iliac crest block grafts were found to be a dependable treatment option for dental implant placement, and placing block grafts outside the bone contour did not lead to inferior outcomes.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".