Marginal bone level change of immediately restored implants with simultaneous guided bone regeneration: A systematic review
Bibliographic record
Abstract
AIM: To assess marginal bone level change (MBLc), clinical outcomes for soft tissue, and survival rates for immediately restored implants with simultaneous guided bone regeneration (GBR). MATERIALS AND METHODS: Electronic and manual searches were conducted in PubMed/MEDLINE, EMBASE, and CENTRAL for studies that investigated immediately restored implants in simultaneously grafted sites with a mean follow-up of over 12 months. MBLc was the primary outcome. Soft tissue clinical parameters and implant survival rate (ISR) were the secondary outcomes. RESULTS: Twenty-five studies (5 randomized controlled trials, 6 prospective studies, 2 retrospective studies, and 12 case series) were included, from which 692 immediately restored implants were analyzed. For studies that investigated bone grafts in the gap between the implant and the peripheral bone wall, the weighted mean MBLc was -0.73 ± 1.52 mm (range: -1.50 to 0.26 mm) for 475 implants. Pink esthetic score (PES) was improved in eight studies and the weighted cumulative ISR was 98.99% (Median: 100%) in 622 implants. Mean MBLc was -1.19 ± 0.26 mm for 30 implants in studies that reported gap with dehiscence and/or fenestration augmentation. Weighted cumulative ISR was 97.25% in 70 implants. A meta-analysis was not possible due to the lack of studies with an eligible control group. Therefore, the data should be interpreted with caution. CONCLUSION: Less marginal bone loss and more predictable soft tissue parameters can be achieved for immediately restored implants with simultaneous peri-implant gap filling compared with gap with dehiscence/fenestration grafting. Increased ISR for implants with gap filling was observed. However, more evidence is needed to confirm whether immediate provisional prostheses should be utilized when bone defects are simultaneously augmented around the implants.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".