Evidence map›Paper›PMID 39399858›Full record

ArticleJournal of clinical and experimental dentistry2024

Effect of Surface Treatments Applied to 3D Printed Permanent Resins on Shear Bond Strength.

Bilge Ersöz, Numan Aydın, Bahadır Ezmek, Serpil Karaoğlanoğlu, İrem-Kübra Çal

Abstract read
In one paragraph

Article in Journal of clinical and experimental dentistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 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

5 authors.

Bilge ErsözDDS, PhD. University of Health Sciences, Gulhane Faculty of Dentistry, Department of Restorative Dental Treatment, Ankara, Turkey.
Numan AydınDDS, PhD. University of Health Sciences, Gulhane Faculty of Dentistry, Department of Restorative Dental Treatment, Ankara, Turkey.
Bahadır EzmekDDS, PhD. University of Health Sciences, Gulhane Faculty of Dentistry, Department of Prosthodontics, Ankara, Turkey.
Serpil KaraoğlanoğluDDS, PhD. University of Health Sciences, Gulhane Faculty of Dentistry, Department of Restorative Dental Treatment, Ankara, Turkey.
İrem-Kübra ÇalDDS. University of Health Sciences, Gulhane Faculty of Dentistry, Department of Restorative Dental Treatment, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 3D-printed permanent resins have recently been introduced to produce permanent restorations. The aim of this study is to evaluate the effect of surface treatment methods on the shear-bond strength (SBS) between 3D-printed permanent resins and adhesive cement. Material and Methods: In this study, samples were produced using digital light projection (DLP) and stereolithography (SLA) 3D printers with two permanent resins (Crowntec, Saremco and Permanent Crown, Formlabs) in accordance with manufacturer guidelines. The samples were separated into three groups: sandblasting, hydrofluoric acid and no surface treatment. The surface profile (Ra, Sa) of the samples was examined with a confocal microscope (Smartproof 5, Zeiss). Then, a self-adhesive resin cement was applied to the samples in a transparent mold (2.38 mm diameter) in accordance with ISO 29022:2013. A universal testing machine was used to perform SBS test. A stereomicroscope was used to analyze the different types of fractures. A two-way analysis of variance (ANOVA) test was used to assess the data ( Results: The samples with sandblasting applied to the surface showed higher surface roughness values than the samples with hydrofluoric acid ( Conclusions: When sandblasting was applied to the surface of the samples prepared using permanent resins, higher adhesion was achieved with adhesive cement.

Identifiers

PMID39399858
PMCPMC11470446

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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.