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A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year

Background: This investigation, based on a 1-year retrospective cohort study, aimed to estimate and validate a prognostic model for ailing and failing implants due to peri-implant disease. Methods: A total of 240 patients (male: 97; female: 143; average age of 57.3 years) with at least one ailing or...

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Autores principales: de Araújo Nobre, Miguel, Salvado, Francisco, Nogueira, Paulo, Rocha, Evangelista, Ilg, Peter, Maló, Paulo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6780417/
https://www.ncbi.nlm.nih.gov/pubmed/31480537
http://dx.doi.org/10.3390/jcm8091352
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author de Araújo Nobre, Miguel
Salvado, Francisco
Nogueira, Paulo
Rocha, Evangelista
Ilg, Peter
Maló, Paulo
author_facet de Araújo Nobre, Miguel
Salvado, Francisco
Nogueira, Paulo
Rocha, Evangelista
Ilg, Peter
Maló, Paulo
author_sort de Araújo Nobre, Miguel
collection PubMed
description Background: This investigation, based on a 1-year retrospective cohort study, aimed to estimate and validate a prognostic model for ailing and failing implants due to peri-implant disease. Methods: A total of 240 patients (male: 97; female: 143; average age of 57.3 years) with at least one ailing or failing implant were included: 120 patients for model derivation and 120 patients for model validation. The primary outcome measure was the implant status: success, defined as the arrest of the disease, or failure defined as implant extraction, prevalence or re-incidence of peri-implant disease). Potential prognostic risk indicators were collected at the baseline evaluation. The relative risk (RR) was estimated for the predictors through logistic regression and the c-statistic (95% confidence interval) was calculated for both derivation and validation sets. The significance level was set at 5%. Results: The risk model retrieved the prognostic factors age (RR = 1.04), history of Periodontitis (RR = 3.13), severe peri-implant disease status (RR = 3.26), implant length (RR = 3.52), early disease development (RR = 3.99), with good discrimination in both the derivation set (0.763 [0.679; 0.847]) and validation set (0.709 [0.616; 0.803]). Conclusions: A prognostic risk model for estimating the outcome of implants with peri-implant disease is available, with a good performance considering the c-statistic evaluation.
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spelling pubmed-67804172019-10-30 A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year de Araújo Nobre, Miguel Salvado, Francisco Nogueira, Paulo Rocha, Evangelista Ilg, Peter Maló, Paulo J Clin Med Article Background: This investigation, based on a 1-year retrospective cohort study, aimed to estimate and validate a prognostic model for ailing and failing implants due to peri-implant disease. Methods: A total of 240 patients (male: 97; female: 143; average age of 57.3 years) with at least one ailing or failing implant were included: 120 patients for model derivation and 120 patients for model validation. The primary outcome measure was the implant status: success, defined as the arrest of the disease, or failure defined as implant extraction, prevalence or re-incidence of peri-implant disease). Potential prognostic risk indicators were collected at the baseline evaluation. The relative risk (RR) was estimated for the predictors through logistic regression and the c-statistic (95% confidence interval) was calculated for both derivation and validation sets. The significance level was set at 5%. Results: The risk model retrieved the prognostic factors age (RR = 1.04), history of Periodontitis (RR = 3.13), severe peri-implant disease status (RR = 3.26), implant length (RR = 3.52), early disease development (RR = 3.99), with good discrimination in both the derivation set (0.763 [0.679; 0.847]) and validation set (0.709 [0.616; 0.803]). Conclusions: A prognostic risk model for estimating the outcome of implants with peri-implant disease is available, with a good performance considering the c-statistic evaluation. MDPI 2019-09-01 /pmc/articles/PMC6780417/ /pubmed/31480537 http://dx.doi.org/10.3390/jcm8091352 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
de Araújo Nobre, Miguel
Salvado, Francisco
Nogueira, Paulo
Rocha, Evangelista
Ilg, Peter
Maló, Paulo
A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year
title A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year
title_full A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year
title_fullStr A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year
title_full_unstemmed A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year
title_short A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year
title_sort prognostic model for the outcome of nobel biocare dental implants with peri-implant disease after one year
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6780417/
https://www.ncbi.nlm.nih.gov/pubmed/31480537
http://dx.doi.org/10.3390/jcm8091352
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