Evidence map›Paper›PMID 37443609›Full record

ArticleDiagnostics (Basel, Switzerland)2023

Access Cavity Preparation and Localization of Root Canals Using Guides in 3D-Printed Teeth with Calcified Root Canals: An In Vitro CBCT Study.

Kıvanç Kamburoğlu, Gül Sönmez, Cemre Koç, Funda Yılmaz, Osman Tunç, Abulfaz Isayev

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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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

6 authors.

Kıvanç KamburoğluDepartment of Dentomaxillofacial Radiology, Faculty of Dentistry, Ankara University, 06560 Ankara, Turkey.ORCID 0000-0002-4134-5756
Gül SönmezDepartment of Dentomaxillofacial Radiology, Faculty of Dentistry, Ada Kent University, 33010 Mersin, Turkey.
Cemre KoçDepartment of Endodontics, Faculty of Dentistry, Adnan Menderes University, 09010 Aydın, Turkey.
Funda YılmazDepartment of Endodontics, Faculty of Dentistry, Ankara University, 06500 Ankara, Turkey.
Osman TunçBTech Innovation, Teknokent METU, 06800 Ankara, Turkey.
Abulfaz IsayevSchool of Dental Medicine, Boston University, Boston, MA 02118, USA.

Funding

Ankara University 18B0234001
6 · The paper itself

Abstract

Pulp canal obliteration (PCO) is a significant complication in endodontics that can occur due to various factors. Cone beam computed tomography (CBCT) is a useful diagnostic tool for identifying root canal anatomy and variations, and guided endodontics is emerging as an alternative treatment solution for teeth with partially or entirely obliterated pulpal canals. However, the accuracy of CBCT-guided 3D-printed guides on different materials and layer thicknesses is not well understood. Therefore, this study aimed to evaluate the accuracy of guides prepared using CBCT images on 3D-printed teeth with stereolithography (SLA) using three different materials and two different layer thicknesses. This study found that 3D-printed guides were accurate and reliable for accessing 3D-manufactured obliterated teeth and reaching the apical area. No significant differences in distance or angle measurements were found when different guide materials were used, suggesting that materials can be selected based on availability and cost. These findings contribute to the knowledge base regarding the effectiveness of 3D printing technology in guided endodontics and can help to identify the most suitable materials and techniques for this application.

Indexed as

3D printingaccess cavityCBCTguided endodonticspulp canal obliteration

Identifiers

PMID37443609
PMCPMC10340585

What OpenQuestion holds

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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.