Fracture strength and restorative success of anterior teeth restored and endodontically treated, associated with the use or not of intraradicular fiber post: systematic review

• Grant number: 18/11343-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date until: August 01, 2018
• End date until: July 31, 2019
• Field of knowledge: Health Sciences - Dentistry - Dental Clinics
• Principal Investigator: Taciana Marco Ferraz Caneppele
• Grantee: Kamilla Alves Santos
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Estadual Paulista (UNESP). Campus de São José dos Campos. São José dos Campos , SP, Brazil

Abstract

In the aesthetic rehabilitation of anterior teeth, there are many endodontically treated teeth which need to receive extensive restorations. The loss of tooth structure due to the restorative procedure and cavity access to endodontic treatment can decrease dental strength. The use of intraradicular fiber posts has been proposed to decrease the risks of dental fracture and improve restorative success rates. The objective of this systematic review is to evaluate the fracture strength and restorative success of anterior restored teeth and endodontically treated, associated with the use or not of intrarradicular fiber posts. A systematic review of in vitro studies, randomized clinical trials, controlled clinical studies, and observational studies will be performed. Search strategies will be determined by setting search strategies related to the subject in question in the following databases: MEDLINE via PubMed, Scopus, Web of Science, LILACS, Biblioteca Brasileira em Odontologia (BBO) and The Cochrane Library. Data analysis and extraction will be performed by two reviewers, who will select the potential studies. First, the studies will be selected according to the title and abstract and qualified according to the bias risk analysis. The studies with the best quality will be chosen, and a narrative synthesis will be done based on the data obtained. After data extraction, the heterogeneity of the data will be analyzed and, if possible, a meta-analysis will be performed.