Clinical Performance of Subperiosteal Implants in the Full-Arch Rehabilitation of Severely Resorbed Edentulous Jaws: A Systematic Review and Metanalysis
Bibliographic record
Abstract
Background/Objectives: Subperiosteal implants (SPIs) were first used in the 1940s, but due to their complications and the rise of dental implants, they were discontinued. Thanks to new technologies and new materials, nowadays they are being used again and studied as a treatment for severe bone defects. This review analyzes the clinical results—survival rates and complications—of SPIs used to support full arch rehabilitations of severely resorbed maxillae and mandibles, comparing the outcomes resulting from implant placement conducted in one or two surgical interventions. Methods: An automated search was conducted in four databases (Medline/Pubmed, Scopus, Web of Science, and Cochrane Library), as well as a manual search for relevant clinical articles published before 28 February 2025. The review included human studies with at least four patients, in which SPIs were placed to restore full-arch edentulous maxillae and mandibles. Quality of evidence was evaluated using the Newcastle–Ottawa Quality Assessment Scale and the Joanna Briggs Institute Critical Appraisal tool. Results: A total of 14 studies met the inclusion criteria and were included for analysis, including 958 patients and 973 SPIs. The survival rate was 100% when one surgical intervention was performed and 85% when two interventions were performed after 4–38 months and 3–22 years follow-up, respectively. Conclusions: SPIs would appear to offer a good alternative for patients with severe bone atrophies, especially SPIs fabricated using digital techniques in a single step, presenting promising survival rates and a low complication rate, although more randomized clinical trials with long-term follow-up are needed.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.016 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".