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Use of Self-Adhesive Resin Cements in Dentistry: a Literature Review

2021· review· en· W3137981596 on OpenAlexaff
João Marcos Carvalho Silva, Raíssa Alves Feitosa, Danyege Lima Araújo Ferreira, Mila Oliveira Santos Viana

Bibliographic record

VenueJournal of Health Sciences · 2021
Typereview
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsPROTO Manufacturing (Canada)
Fundersnot available
KeywordsAdhesiveCementation (geology)BiocompatibilityMaterials scienceDentistryDental cementAdhesionCementComposite materialMedicineMetallurgy

Abstract

fetched live from OpenAlex

AbstractSelf-adhesive resin cements (SARCs) are cementing agents and have the objective of simplifying adhesive cementation, with a simplified use protocol. The aim of this article was to review the literature on SARCs with a focus on the advantages of their use, highlighting their adhesion and biocompatibility mechanism. Thus, the Health Sciences Descriptors “Self-Adhesive Resin Cement”, “Dental Cements”, “Adhesion” and “Dental Prosthesis” were used, as well as their Portuguese counterparts in the online databases SciELO, PubMed and Bireme in the period of time between the years 2000 to 2020. According to the studies, SARCs have excellent physical and mechanical properties, which include low solubility in the oral environment, adhesion to the dental substrate and the prosthetic part, color mimicry, biocompatibility and fluoride release, in addition to being applied in a single step, optimizing the operator's working time. In addition, self-adhesive cements seem to offer a promising new approach in indirect restorative procedures, which may present a performance similar to conventional ones, however more studies are needed to support their long-term applicability. Keywords: Resin Cements. Dental Cements. Adhesion. Dental Prosthesis. ResumoOs cimentos resinosos autoadesivos (CRAAs) são agentes de cimentação e possuem o objetivo de simplificar a cimentação adesiva, com um protocolo simplificado de utilização. Assim, o objetivo deste trabalho foi revisar na literatura acerca dos CRAAs com enfoque nas vantagens de sua adequada utilização, evidenciando seu mecanismo de adesão e biocompatibilidade. Dessa forma, foram utilizados os descritores em Ciências da Saúde (DeCS) “Cimento Resinoso Autoadesivo”, “Cimentos Dentários”, “Adesão” e “Prótese Dentária”, assim como seus correspondentes na língua inglesa nas bases de dados online SciELO, PubMed e Bireme no período de tempo entre os anos 2000 a 2020. De acordo com os estudos, os CRAAs apresentam excelentes propriedades físicas e mecânicas, que incluem baixa solubilidade no meio bucal, adesão ao substrato dental e a peça protética, mimetização de cores, biocompatibilidade e liberação de fluoretos, além de serem aplicados em uma única etapa clínica, otimizando o tempo de trabalho do operador. Além disso, os cimentos autoadesivos oferecem uma nova abordagem promissora em procedimentos restauradores indiretos, podendo apresentar um desempenho semelhante aos convencionais, porém são necessários mais estudos que sustentem sua aplicabilidade a longo prazo. Palavras-chave: Cimentos de Resina. Cimentos Dentários. Adesão. Prótese Dentária.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0120.014
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.158
GPT teacher head0.457
Teacher spread0.300 · 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 designNot applicable
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

Citations5
Published2021
Admission routes1
Has abstractyes

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