Evidence map›Paper›PMID 33993877›Full record

ArticleBMC oral health2021

Investigating inlay designs of class II cavity with deep margin elevation using finite element method.

Yung-Chung Chen, Chi-Lun Lin, Chun-Hsien Hou

Abstract read
In one paragraph

Article in BMC oral health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yung-Chung ChenSchool of Dentistry and Institute of Oral Medicine, Medical College, National Cheng Kung University, Tainan, Taiwan, Republic of China.
Chi-Lun LinDepartment of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan, Republic of China. linc@ncku.edu.tw.
Chun-Hsien HouDepartment of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan, Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study evaluates the mechanical performance of deep margin elevation technique for carious cavities by considering the shape designs and material selections of inlay using a computational approach combined with the design of experiments method. The goal is to understand the effects of the design parameters on the deep margin elevation technique and provide design guidelines from the biomechanics perspective.

methodsSeven geometric design parameters for defining an inlay's shape of a premolar were specified, and the influence of cavity shape and material selection on the overall stress distribution was investigated via automated modelling. Material selection included composite resin, ceramic, and lithium disilicate. Finite element analysis was performed to evaluate the mechanical behavior of the tooth and inlay under a compressive load. Next, the analysis of variance was conducted to identify the parameters with a significant effect on the stress occurred in the materials. Finally, the response surface method was used to analyze the stress responses of the restored tooth with different design parameters.

resultsThe restored tooth with a larger isthmus width demonstrated superior mechanical performance in all three types of inlay materials, while the influence of other design parameters varied with the inlay material selection. The height of the deep margin elevation layer insignificantly affected the mechanical performance of the restored tooth.

conclusionsA proper geometric design of inlay enhances the mechanical performance of the restored tooth and could require less volume of the natural dentin to be excavated. Furthermore, under the loading conditions evaluated in this study, the deep margin elevation layer did not extensively affect the strength of the tooth structure.

Indexed as

Dental CariesInlaysCeramicsComposite ResinsDental Stress AnalysisFinite Element AnalysisHumansMaterials TestingStress, MechanicalComposite ResinsDental cavity preparationsDental inlayFinite element analysis

Identifiers

PMID33993877
PMCPMC8127254

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.