Evidence map›Paper›PMID 39049657›Full record

ArticleHua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology2024

Effect of laser and coating surface treatment on the bond strength of zirconia ceramics.

Qiao Du, Guangliang Niu

Abstract read
In one paragraph

Article in Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
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

2 authors.

Qiao DuDept. of Stomatology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing 100039, China.
Guangliang NiuDept. of Stomatology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing 100039, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aims to investigate bond strength between zirconia and resin cement through surface treatments with Er: YAG laser, Nd: YAG laser, and Si-Zr coating.

methodsSeventy-five round pre-sintered zirconia discs with a diameter of 18 mm and a thickness of 1.5 mm were prepared by a powder compactor. Fifty discs were randomly divided into five groups of 10 discs each and were subjected to five surface treatments: no treatment (control group), sandblasting with alumina particles (sandblasting group), Er: YAG laser treatment (Er: YAG laser group), Nd:YAG laser treatment (Nd: YAG laser group), and Si-Zr coating treatment (Si-Zr coating group). The discs were then bonded to composite resin columns with resin cement. The shear bond strength of each group was tested with a universal tester. Roughness tester, scanning electron microscope (SEM), and energy dispersive spectroscopy were used to analyze surface performance.

resultsThe bond strength of the Si-Zr coating group was higher than that of the remaining groups (

conclusionsEr: YAG laser and Nd: YAG laser treatment on the zirconia ceramic surface could increase roughness and improve the bond strength to resin cement. Si-Zr coating treatment is an effective alternative for increasing the roughness and bond strength of zirconia surface and is superior to sandblasting and laser treatments.

Indexed as

CeramicsLasers, Solid-StateMaterials TestingSurface PropertiesZirconiumComposite ResinsDental BondingDental Stress AnalysisMicroscopy, Electron, ScanningShear StrengthSiliconComposite ResinsSiliconZirconiumzirconium oxidebond strengthcoatinglasersurface treatmentzirconia

Identifiers

PMID39049657
PMCPMC11190862

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.