Current Insights on Fiber Posts: A Narrative Review of Laboratory and Clinical Studies
Bibliographic record
Abstract
PURPOSE: The aim of this study was to review the literature related to the clinical performance and laboratory findings regarding fiber posts, as well as the cementation technique employed with their use. MATERIALS AND METHODS: A literature search was performed using an electronic database, PubMed/Medline, between 2010 and 2023. The terms used were "intra coronal post, fiber post, post cementation, and post length". Titles and abstracts were initially screened, and a full-text assessment was conducted for those that fulfilled the inclusion criteria. The reference list of the collected papers was also screened for further relevant citations. RESULTS: In this work, 135 potentially eligible studies were analyzed. Titles and abstracts of 90 studies followed the inclusion criteria and were selected for a full-text assessment, resulting in 50 studies selected. Moreover, additional studies from relevant citations were included, totaling 57 studies. CONCLUSION: According to the laboratory and clinical studies revised, the survival rate between fiber and prefabricated and cast metal posts was similar, and failures were mainly related to the loss of retention. The intra-canal post length of less than two-thirds of the root length presented successful results when ferrule was present. Furthermore, the ferrule increased the longevity of teeth restored with fiber posts. Additionally, the use of a surface treatment protocol for fiber posts and the adhesive cementation technique both contributed to the clinical success and longevity of the intra-canal post.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".