Long‐term outcomes of post‐extraction alveolar ridge preservation and alveolar ridge reconstruction followed by delayed implant placement: A systematic review
Bibliographic record
Abstract
This systematic review analyzed the long-term outcomes of alveolar ridge preservation (ARP) and alveolar ridge reconstruction (ARR) before delayed implant placement. Eight studies were included (one non-randomized clinical trial, one prospective case series, four retrospective comparative studies, and two retrospective case series). Risk of bias assessment, using a modified Newcastle-Ottawa Scale, revealed one high-quality study, four medium-quality studies, and three with low methodological quality. In total, 333 patients underwent ARP or ARR, with the most common approach involving xenogeneic bone grafting and socket sealing with a collagen membrane, matrix, or dressing. Follow-up ranged from 5 to 10 years. Due to methodological heterogeneity and limited data, quantitative analysis was not feasible. The implant survival rate was the most frequently reported outcome, followed by peri-implant marginal bone level changes and peri-implant disease incidence. Despite limited evidence, ARP and ARR appear to support favorable long-term outcomes, particularly in implant survival and bone stability. Further well-designed, large-scale studies comparing different ARP and ARR modalities with other therapies are needed to guide clinical decision-making.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".