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Record W2897424535 · doi:10.1111/jerd.12431

Five‐year success rate of resin‐bonded fixed partial dentures: A systematic review

2018· review· en· W2897424535 on OpenAlexaffabout
Islam Abd Alraheam, Caroline Nguyen Ngoc, Christopher Wiesen, Terence E. Donovan

Bibliographic record

VenueJournal of Esthetic and Restorative Dentistry · 2018
Typereview
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDenturesDentistryOrthodonticsMaterials scienceMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess and compare the 5-year success rate of resin-bonded fixed partial dentures (RBFPDs) fabricated from different materials. METHODS: An electronic search on 3 databases from January 1965 to March of 2017 was done for human randomized clinical trials (RCTs), and prospective and retrospective cohort studies. The key words used in the search were: Bridge OR bridges OR fixed partial OR fixed dental AND resin bonded OR Maryland OR ceramic bonded. Quality assessment was done using the Newcastle-Ottawa scale. Success was defined as the RBFPDs remaining in situ and not having experienced debonding, biological failures, or mechanical failures at the examination visit. RESULTS: Meta analyses of the included studies showed an estimated 5-year success rate of 88.18% for the metal framework RBFPDs and 84.41% for the nonmetal framework RBFPDs. The estimated 5-year success rate for each nonmetal material category was 92.07% for zirconia, 94.26% for In-Ceram alumina, and 84.83% for fiber-reinforced composite. The failure rate was not statistically significant among the single, double, and multiple retainers RBFPDs (P > .05). Technical complications were the main reason for failures. CONCLUSION: The 5-year clinical performance of RBFPDs is similar to the performance of conventional fixed partial dentures (FPDs) and implant-supported crowns. CLINICAL SIGNIFICANCE: Clinicians should consider using RBFPDs more often because their clinical performance is similar to the performance of conventional FPDs and implant-supported crowns.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.109
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.356
Teacher spread0.320 · 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 teacher head, not a consensus.

Study designSystematic review
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".

Quick stats

Citations72
Published2018
Admission routes2
Has abstractyes

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