Evidence map›Paper›PMID 41146159›Full record

ArticleBMC oral health2025

Wear of interim resin materials manufactured by 3D printing and CAD/CAM milling following chewing simulation.

Yelda Çiçek, Ceren Küçük

Abstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

2 authors.

Yelda ÇiçekDepartment of Prosthodontics, Faculty of Dentistry, University of Marmara, Basibuyuk Street 9/3, Maltepe, Istanbul, 34854, Turkey.
Ceren KüçükDepartment of Prosthodontics, Faculty of Dentistry, University of Marmara, Basibuyuk Street 9/3, Maltepe, Istanbul, 34854, Turkey. ceren.kucuk@marmara.edu.tr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecently introduced novel additively manufactured interim resins require in vitro investigation of their mechanical properties. The objective of the study is to assess the wear rates of four different interim resin materials using a chewing simulator for 1.5 months of dynamic loading.

methodsFour interim resin materials were assessed: (1) Liquid crystal displays (LCD) 3D printed (n = 8), (2) Digital light processing (DLP) 3D printed (n = 8) (3) Conventional autopolymerizing bis-acrylic (n = 8), (4) CAD/CAM milled interim resin materials. The specimens underwent 30,000 cycles, approximately equivalent to 1.5 months of chewing simulation. The volumetric loss (mm

resultsThe mean ± SD wear volume losses (mm3) following chewing simulation were 0.1394 ± 0.0810 for conventional resin, 0.1099 ± 0.0873 for milled resin, 0.0980 ± 0.1021 for DLP resin, and 0.0934 ± 0.0788 for LCD resin. Wear volume loss was not significantly different amongst interim materials (P > 0.05). The mean ± SD wear depths (mm) following chewing simulation were 0.4084 ± 0.01440 for conventional resin, 0.4343 ± 0.1115 for milled resin, 0.4546 ± 0.0349 for DLP resin, and 0.3954 ± 0.1051 for LCD resin. Wear depths were not significantly different amongst interim materials (P > 0.05).

conclusions3D printed and CAD/CAM milled resins had wear resistance comparable to conventional resin. Wear resistance after chewing simulation offers 3D printed resin a suitable interim restorative material for clinical use.

Indexed as

Computer-Aided DesignDental MaterialsDental Restoration WearMasticationPrinting, Three-DimensionalAcrylic ResinsComposite ResinsHumansMaterials TestingAcrylic ResinsComposite ResinsDental Materials3D printingCAD/CAMInterim crownProvisional restorationResinWear

Identifiers

PMID41146159
PMCPMC12560444

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Registered trials

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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.