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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-6780417 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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