Framework Materials for Full-Arch Implant-Supported Rehabilitations: A Systematic Review of Clinical Studies
Bibliographic record
Abstract
The purpose of this systematic review was to investigate the clinical outcomes of frameworks made of different materials in patients with implant-supported full-arch prostheses. A literature search was conducted on MEDLINE, Scopus and Cochrane Library, until the 1st of March 2021, with the following search terms: framework or substructure combined with "dental implants". The outcomes evaluated were: implant and prosthesis survival, bone resorption, biological and technical complications. The Cochrane Handbook for Systematic Reviews of Interventions was employed to assess the risk of bias in randomized clinical trials. The Newcastle-Ottawa quality assessment scale was used for non-randomized studies. In total, 924 records were evaluated for title and abstract, and 11 studies were included in the review: 4 clinical randomized trials and 7 cohort studies. The framework materials investigated were: gold alloy, titanium, silver-palladium alloy, zirconia and polymers including acrylic resin and carbon-fiber-reinforced composites. High implant and prosthetic cumulative survival rates were recorded by all included studies. Various materials and different fabrication techniques are now available as alternatives to traditional cast metal frameworks, for full-arch implant-supported rehabilitations. Further long-term studies are needed to validate the use of these materials and clarify their specific clinical indications and manufacturing protocols to optimize their clinical outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".