Complications associated with vertical bone augmentation techniques in implant dentistry: A systematic review of clinical studies published in the last ten years
Bibliographic record
Abstract
Vertical bone augmentation procedures are increasingly necessary in daily practice. However, it has been reported that vertical ridge augmentation is one of the least predictable techniques in terms of complications. The aim of this systematic review was to evaluate and compare complications in relation to the different procedures used for vertical bone augmentation prior to implant placement. This review was conducted according to PRISMA guidelines. An electronic search was carried out in four databases: The National Library of Medicine (MEDLINE/PubMed); Web of Science; SCOPUS; and Cochrane Central Register of Controlled Trials (CENTRAL). The Newcastle-Ottawa Quality Assessment Scale, the Cochrane Collaboration tool for assessing risk of bias, and The Joanna Briggs Institute Critical Appraisal tool were used to assess the quality of evidence in the studies reviewed. Twenty-five studies with a total of 749 vertically augmented sites were included in the review. Complication rates varied among the different procedures: 51.02% for distraction osteogenesis, 38.01% for bone blocks, and 16.80% for guided bone regeneration. Vertical bone augmentation procedures prior to implant placement are associated with frequent surgical complications and should be approached with caution due to their possible impact on clinical treatment success.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".