Clinical behavior and complications of CAD-CAM subperiosteal implants supporting fixed partial restorations: a scoping review
Bibliographic record
Abstract
Purpose This scoping review evaluates the clinical performance of subperiosteal implants (SPIs) used to support fixed partial restorations (FPRs) in patients with severe bone atrophy. The study focuses on survival rates and complications (biological and mechanical) associated with SPIs, aiming to fill a gap in the literature regarding their use in partial restorations. Background SPIs are an alternative for patients with significant bone loss, avoiding the need for extensive bone grafting required by traditional implants. Despite their potential, there is limited evidence on SPIs for partial restorations, especially regarding long-term outcomes. Methodology Following PRISMA-ScR guidelines, the review included studies from Medline/PubMed, Web of Science, Cochrane Library, and Scopus up to December 2024. Studies with at least three patients and one-year follow-up were included. Data on survival rates and complications were extracted, and study quality was assessed using the Joanna Briggs Institute's Critical Appraisal Tool and Newcastle-Ottawa Scale. Expected Outcomes The expected outcomes of this research include: Comprehensive Mapping of Evidence: This review will provide a detailed overview of the current evidence on SPIs supporting FPRs, including survival rates and complications. Identification of Knowledge Gaps: The review will highlight areas where further research is needed, particularly in terms of long-term outcomes and comparative studies with other implant techniques. Clinical Implications: The findings will help clinicians make informed decisions about the use of SPIs in patients with severe bone atrophy, particularly when conventional implants are not viable.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".