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A prosthodontic-based implant patient classification system.

Identifieur interne : 004655 ( PubMed/Corpus ); précédent : 004654; suivant : 004656

A prosthodontic-based implant patient classification system.

Auteurs : S R Davidoff ; M A Steinberg

Source :

RBID : pubmed:8374711

English descriptors

Abstract

Success in dental implant-supported prostheses has traditionally been measured in terms of successful osseointegration of implant fixtures. Clearly, this is not the true measure of success in terms of patient expectations. Patients expect prostheses with which they can function, without embarrassment or insecurity. Therefore, patient evaluation and treatment planning must be concerned with final prosthetic results and how patients will look and function. This article introduces a simple classification system that will help eliminate confusion in treatment-planning with implant patients and will also allow dentists to better advise patients about the goals of treatment. The classification system is based primarily on the prosthetic design that patients will receive and offers a means of quantitating the complexity and, therefore, the predictability of treatment.

PubMed: 8374711

Links to Exploration step

pubmed:8374711

Le document en format XML

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<div type="abstract" xml:lang="en">Success in dental implant-supported prostheses has traditionally been measured in terms of successful osseointegration of implant fixtures. Clearly, this is not the true measure of success in terms of patient expectations. Patients expect prostheses with which they can function, without embarrassment or insecurity. Therefore, patient evaluation and treatment planning must be concerned with final prosthetic results and how patients will look and function. This article introduces a simple classification system that will help eliminate confusion in treatment-planning with implant patients and will also allow dentists to better advise patients about the goals of treatment. The classification system is based primarily on the prosthetic design that patients will receive and offers a means of quantitating the complexity and, therefore, the predictability of treatment.</div>
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