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Modelling changes in clinical attachment loss to classify periodontal disease progression
AIM: The goal of this study was to identify progressing periodontal sites by applying linear mixed models (LMM) to longitudinal measurements of clinical attachment loss (CAL). METHODS: Ninety‐three periodontally healthy and 236 periodontitis subjects had their CAL measured bi‐monthly for 12 months....
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021116/ https://www.ncbi.nlm.nih.gov/pubmed/26935472 http://dx.doi.org/10.1111/jcpe.12539 |
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author | Teles, Ricardo Benecha, Habtamu K. Preisser, John S. Moss, Kevin Starr, Jacqueline R. Corby, Patricia Genco, Robert Garcia, Nathalia Giannobile, William V. Jared, Heather Torresyap, Gay Salazar, Elida Moya, Julie Howard, Cynthia Schifferle, Robert Falkner, Karen L. Gillespie, Jane Dixon, Debra Cugini, MaryAnn |
author_facet | Teles, Ricardo Benecha, Habtamu K. Preisser, John S. Moss, Kevin Starr, Jacqueline R. Corby, Patricia Genco, Robert Garcia, Nathalia Giannobile, William V. Jared, Heather Torresyap, Gay Salazar, Elida Moya, Julie Howard, Cynthia Schifferle, Robert Falkner, Karen L. Gillespie, Jane Dixon, Debra Cugini, MaryAnn |
author_sort | Teles, Ricardo |
collection | PubMed |
description | AIM: The goal of this study was to identify progressing periodontal sites by applying linear mixed models (LMM) to longitudinal measurements of clinical attachment loss (CAL). METHODS: Ninety‐three periodontally healthy and 236 periodontitis subjects had their CAL measured bi‐monthly for 12 months. The proportions of sites demonstrating increases in CAL from baseline above specified thresholds were calculated for each visit. The proportions of sites reversing from the progressing state were also computed. LMM were fitted for each tooth site and the predicted CAL levels used to categorize sites regarding progression or regression. The threshold for progression was established based on the model‐estimated error in predictions. RESULTS: Over 12 months, 21.2%, 2.8% and 0.3% of sites progressed, according to thresholds of 1, 2 and 3 mm of CAL increase. However, on average, 42.0%, 64.4% and 77.7% of progressing sites for the different thresholds reversed in subsequent visits. Conversely, 97.1%, 76.9% and 23.1% of sites classified as progressing using LMM had observed CAL increases above 1, 2 and 3 mm after 12 months, whereas mean rates of reversal were 10.6%, 30.2% and 53.0% respectively. CONCLUSION: LMM accounted for several sources of error in longitudinal CAL measurement, providing an improved method for classifying progressing sites. |
format | Online Article Text |
id | pubmed-5021116 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-50211162016-09-23 Modelling changes in clinical attachment loss to classify periodontal disease progression Teles, Ricardo Benecha, Habtamu K. Preisser, John S. Moss, Kevin Starr, Jacqueline R. Corby, Patricia Genco, Robert Garcia, Nathalia Giannobile, William V. Jared, Heather Torresyap, Gay Salazar, Elida Moya, Julie Howard, Cynthia Schifferle, Robert Falkner, Karen L. Gillespie, Jane Dixon, Debra Cugini, MaryAnn J Clin Periodontol Periodontal Diseases AIM: The goal of this study was to identify progressing periodontal sites by applying linear mixed models (LMM) to longitudinal measurements of clinical attachment loss (CAL). METHODS: Ninety‐three periodontally healthy and 236 periodontitis subjects had their CAL measured bi‐monthly for 12 months. The proportions of sites demonstrating increases in CAL from baseline above specified thresholds were calculated for each visit. The proportions of sites reversing from the progressing state were also computed. LMM were fitted for each tooth site and the predicted CAL levels used to categorize sites regarding progression or regression. The threshold for progression was established based on the model‐estimated error in predictions. RESULTS: Over 12 months, 21.2%, 2.8% and 0.3% of sites progressed, according to thresholds of 1, 2 and 3 mm of CAL increase. However, on average, 42.0%, 64.4% and 77.7% of progressing sites for the different thresholds reversed in subsequent visits. Conversely, 97.1%, 76.9% and 23.1% of sites classified as progressing using LMM had observed CAL increases above 1, 2 and 3 mm after 12 months, whereas mean rates of reversal were 10.6%, 30.2% and 53.0% respectively. CONCLUSION: LMM accounted for several sources of error in longitudinal CAL measurement, providing an improved method for classifying progressing sites. John Wiley and Sons Inc. 2016-04-06 2016-05 /pmc/articles/PMC5021116/ /pubmed/26935472 http://dx.doi.org/10.1111/jcpe.12539 Text en © 2016 The Authors. Journal of Clinical Periodontology Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Periodontal Diseases Teles, Ricardo Benecha, Habtamu K. Preisser, John S. Moss, Kevin Starr, Jacqueline R. Corby, Patricia Genco, Robert Garcia, Nathalia Giannobile, William V. Jared, Heather Torresyap, Gay Salazar, Elida Moya, Julie Howard, Cynthia Schifferle, Robert Falkner, Karen L. Gillespie, Jane Dixon, Debra Cugini, MaryAnn Modelling changes in clinical attachment loss to classify periodontal disease progression |
title | Modelling changes in clinical attachment loss to classify periodontal disease progression |
title_full | Modelling changes in clinical attachment loss to classify periodontal disease progression |
title_fullStr | Modelling changes in clinical attachment loss to classify periodontal disease progression |
title_full_unstemmed | Modelling changes in clinical attachment loss to classify periodontal disease progression |
title_short | Modelling changes in clinical attachment loss to classify periodontal disease progression |
title_sort | modelling changes in clinical attachment loss to classify periodontal disease progression |
topic | Periodontal Diseases |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021116/ https://www.ncbi.nlm.nih.gov/pubmed/26935472 http://dx.doi.org/10.1111/jcpe.12539 |
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