Clinical performance of single implant prostheses restored using titanium base abutments: A systematic review and meta‐analysis
Bibliographic record
Abstract
PURPOSE: The aim of this review was to evaluate the survival rates of restorations utilizing titanium base abutments (TBA) for restoring single-unit implant prostheses. MATERIALS AND METHODS: This review was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The focus question was: In patients who require the restoration of a single dental implant utilizing a titanium base abutment, what are the determining factors and outcomes relating to implant prosthesis prognosis and survival? A comprehensive search of databases (PubMed, EMBASE, and Cochrane Library) was conducted on 16 April 2023 and updated on 5 May 2023. Randomized clinical trials (RCT), retrospective studies and prospective studies, reporting on the use of TBA for single implant prostheses, were reviewed. A Cochrane collaboration risk of bias assessment analysis was performed for randomized clinical studies, and the Newcastle-Ottawa Scale tool was applied for non-randomized studies. A meta-analysis was performed on clinical trials reporting on survival rates of both TBA and other abutments. Other clinical studies, reporting on TBA only, were included for descriptive statistics. RESULTS: 0%; p = .99]. Twenty-three prospective and retrospective studies fulfilled the criteria and were included in the meta-analysis after 12 months of function. A total of 857 single implant-supported prostheses fabricated with a TBA were included. TBA abutments have an estimate 98.6% survival rate after 1 year in function (95% CI: 97.9%-99.4%). The mean follow-up period was 31.2 ± 16.9 months. CONCLUSIONS: Single implant prosthesis restored with titanium base abutments showed favourable short-term survival rates.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.008 | 0.008 |
| 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) | 0.003 | 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".