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Πέμπτη 7 Σεπτεμβρίου 2017

A risk-based decision making tree for managing fractured abutment and prosthetic screws: A systematic review

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Publication date: Available online 6 September 2017
Source:The Journal of Prosthetic Dentistry
Author(s): Ryan M. Mizumoto, Faris Z. Jamjoom, Burak Yilmaz
Statement of problemIn implant dentistry, a variety of techniques are used to manage fractured abutment and prosthetic screws. All of them pose various degrees of difficulty to both the clinician and patient and risk involving damage to the implants and prostheses.PurposeThe purpose of this systematic review was to classify and organize the various reported techniques for managing fractured abutment and or prosthetic screws into a risk-based, decision making tree that could be used to guide the clinician through this difficult and time-consuming clinical procedure.Material and methodsA systematic search of the PubMed/MEDLINE database for articles published before June 2016 was performed by 2 independent reviewers. Studies published in English that described a clinical technique to retrieve or manage a fractured abutment or prosthetic screws were included. Techniques were classified according to risk of irreversible damage to the implant. Low-risk techniques were defined as those involving the use of basic hand instruments and instrument modification; moderate-risk techniques were defined as those involving the use of screw retrieval kits, rotary instruments, and screw modification; and high-risk techniques were defined as those involving modification of the implant. Published techniques were then organized into a decision-making tree.ResultsA total of 35 articles were included. The reported techniques ranged from straightforward instrumentation and instrument modification to screw or implant modifications. Seven techniques were considered low risk, 17 moderate risk, and 11 high risk.ConclusionsThe proposed risk-based decision tree is a useful tool in helping clinicians choose the most appropriate strategy or sequence of strategies that offers maximum benefit to the patient while minimizing associated risks.



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