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Can fiber placement influence the fracture resistance of endodontically treated teeth with indirect partial ceramic restorations? A systematic review and meta-analysis

2025· review· en· W4412391682 on OpenAlexaff
Ali Abidrahamani, Sanaz AziziGermi, Hooman Khanzadeh, Safoura Ghodsi, Marta Revilla‐León, Seyed Ali Mosaddad

Bibliographic record

VenueJournal of Prosthetic Dentistry · 2025
Typereview
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMeta-analysisDentistryCochrane LibraryMaterials scienceOrthodonticsMolarMedicineInternal medicine

Abstract

fetched live from OpenAlex

STATEMENT OF PROBLEM: Restoring endodontically treated teeth with indirect partial ceramic restorations poses biomechanical challenges associated with the compromised tooth structure, and the potential role of fiber reinforcement in improving fracture resistance remains unclear. PURPOSE: The purpose of this systematic review and meta-analysis was to determine whether reinforcing the endodontically treated tooth structures with fiber ribbons or short fiber-reinforced resin composites (SFRCs) increases the fracture resistance of indirect partial ceramic restorations. MATERIAL AND METHODS: A database search was conducted in PubMed, Embase, Scopus, Web of Science, and Cochrane Library up to November 2024. Eligible in vitro studies assessed the fracture resistance of indirect partial ceramic restorations in endodontically treated premolars or molars by comparing fiber-reinforced (FR) and nonfiber-reinforced (NFR) teeth. Exclusions included studies on direct resin composites, foundation restorations, indirect resin composites, nonrestorative specimens, or nonendodontically treated teeth. Data were analyzed using a random-effects model, with subgroup analyses conducted to identify potential sources of heterogeneity (α=.05). Sensitivity analysis and the Egger regression test were used to evaluate reliability and publication bias. Methodological quality was assessed using the QUIN Tool. RESULTS: Of 3299 records, 7 articles were included. Three meta-analyses were conducted, including an overall analysis of SFRCs and fiber ribbons, along with separate analyses for each. The overall analysis revealed no significant differences between FR and NFR groups (SMD: 0.21, 95% CI: [-0.51, 0.92], I²=88.39%, P<.001). The SFRC analysis also showed no significant differences (SMD: 0.06, 95% CI: [-0.98, 1.10], P=.905), with high heterogeneity (I²=91.92%, P<.001). The fiber ribbon analysis revealed significant differences (SMD: 0.63, 95% CI: [0.16, 1.10], P=.009), with low heterogeneity (I²=22.83%, P=.248). CONCLUSIONS: Fiber ribbons showed promise for enhancing the fracture resistance of indirect partial ceramic restorations in endodontically treated posterior teeth.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0130.031
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.030
GPT teacher head0.324
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

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Citations2
Published2025
Admission routes1
Has abstractno

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