Multidimensional 3D-Printed Scaffolds for Ridge Preservation and Dental Implant Placement: A Systematic Review
Bibliographic record
Abstract
Background: Regenerative medicine in dentistry involves tissue engineering applications suitable for the unique oral environment. In this regard, advances in computer-aided technology have facilitated the creation of 3D scaffolds using cone beam computed tomography (CBCT). This review aimed to investigate whether 3D-printed scaffolds can be effectively used to achieve ridge preservation and/or predictable vertical and horizontal bone augmentation, ensuring successful outcomes for dental implant placement. Methods: A comprehensive search was conducted across six electronic databases (PubMed, Scopus, ScienceDirect, Google Scholar, Web of Science, Ovid) to identify relevant studies according to specific eligibility criteria, following the PRISMA guidelines. Two independent reviewers screened and selected studies, performed data extraction, and assessed the risk of bias using the Cochrane tool for randomized clinical trials and the Newcastle–Ottawa Scale for non-randomized clinical trials. Results: The initial search yielded 419 articles, which were subsequently screened to remove duplicates. After evaluating 293 articles based on title and abstract, 10 studies remained for full-text assessment. Ultimately, only three studies met all the pre-established eligibility criteria. Conclusions: The studies included in this systematic review showed that the use of multidimensional customized scaffolds appears to promote dental implant placement. Nevertheless, despite the positive reported effects, further well-designed randomized clinical trials are necessary to determine the special characteristics of the optimal 3D-customized scaffold.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".