Comparison of morbidity‐related parameters between autologous and allogeneic bone grafts for alveolar ridge augmentation from patients' perspective—A questionnaire‐based cohort study
Bibliographic record
Abstract
INTRODUCTION: Alveolar ridge augmentation is often required before dental implant placement. In this context, autologous bone grafts are considered the biological gold standard. Still, bone block harvesting is accompanied by some serious potential disadvantages and possible complications, such as pain, bleeding, and nerve irritation. Several studies aimed to compare autologous to allogeneic bone grafts concerning bone quality and implant survival rates; this is the first prospective study analyzing and comparing morbidity-related parameters after alveolar ridge augmentation using autogenous and allogeneic bone blocks from patients' perspective. METHODS: Using a questionnaire, 36 patients were asked to evaluate the surgery as well as the post-operative period concerning pain, stress, sensibility deficits, satisfaction with, and consequences from the surgery as well as the preferred procedure for future alveolar ridge augmentations. RESULTS: No significant differences were shown regarding stress and pain during and after surgery, whereas the rate of nerve irritations was twice as high in the autologous group. The swelling was significantly higher in patients with autologous bone blocks (p = 0.001). Nevertheless, the overall satisfaction of patients of both groups was very high, with over 8/10 points. CONCLUSIONS: The swelling was the main reason for patients' discomfort in both groups and was significantly higher after autologous bone augmentation. Since this side effect seems to be a highly relevant factor for patients' comfort and satisfaction, it needs to be discussed during preoperative consultation to allow shared decision-making considering the anticipated morbidity.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".