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Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva
This study aims to investigate and assess salivary biomarkers and microbial profiles as a means of diagnosing periodontitis. A total of 121 subjects were included: 28 periodontally healthy subjects, 24 with Stage I periodontitis, 24 with Stage II, 23 with Stage III, and 22 with Stage IV. Salivary pr...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602207/ https://www.ncbi.nlm.nih.gov/pubmed/33066545 http://dx.doi.org/10.3390/diagnostics10100820 |
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author | Lee, Jungwon Lee, Jun-Beom Song, Hyun-Young Son, Min Jung Li, Ling Rhyu, In-Chul Lee, Yong-Moo Koo, Ki-Tae An, Jung-Sub Kim, Jin Sup Kim, Eunkyung |
author_facet | Lee, Jungwon Lee, Jun-Beom Song, Hyun-Young Son, Min Jung Li, Ling Rhyu, In-Chul Lee, Yong-Moo Koo, Ki-Tae An, Jung-Sub Kim, Jin Sup Kim, Eunkyung |
author_sort | Lee, Jungwon |
collection | PubMed |
description | This study aims to investigate and assess salivary biomarkers and microbial profiles as a means of diagnosing periodontitis. A total of 121 subjects were included: 28 periodontally healthy subjects, 24 with Stage I periodontitis, 24 with Stage II, 23 with Stage III, and 22 with Stage IV. Salivary proteins (including active matrix metalloproteinase-8 (MMP-8), pro-MMP-8, total MMP-8, C-reactive protein, secretory immunoglobulin A) and planktonic bacteria (including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas nigrescens, Parvimonas micra, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, Streptococcus mutans, Staphylococcus aureus, Enterococcus faecalis, and Actinomyces viscosus) were measured from salivary samples. The performance of the diagnostic models was assessed by receiver operating characteristics (ROCs) and area under the ROC curve (AUC) analysis. The diagnostic models were constructed based on the subjects’ proteins and/or microbial profiles, resulting in two potential diagnosis models that achieved better diagnostic powers, with an AUC value > 0.750 for the diagnosis of Stages II, III, and IV periodontitis (Model PA-I; AUC: 0.796, sensitivity: 0.754, specificity: 0.712) and for the diagnosis of Stages III and IV periodontitis (Model PA-II; AUC: 0.796, sensitivity: 0.756, specificity: 0.868). This study can contribute to screening for periodontitis based on salivary biomarkers. |
format | Online Article Text |
id | pubmed-7602207 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76022072020-11-01 Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva Lee, Jungwon Lee, Jun-Beom Song, Hyun-Young Son, Min Jung Li, Ling Rhyu, In-Chul Lee, Yong-Moo Koo, Ki-Tae An, Jung-Sub Kim, Jin Sup Kim, Eunkyung Diagnostics (Basel) Article This study aims to investigate and assess salivary biomarkers and microbial profiles as a means of diagnosing periodontitis. A total of 121 subjects were included: 28 periodontally healthy subjects, 24 with Stage I periodontitis, 24 with Stage II, 23 with Stage III, and 22 with Stage IV. Salivary proteins (including active matrix metalloproteinase-8 (MMP-8), pro-MMP-8, total MMP-8, C-reactive protein, secretory immunoglobulin A) and planktonic bacteria (including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas nigrescens, Parvimonas micra, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, Streptococcus mutans, Staphylococcus aureus, Enterococcus faecalis, and Actinomyces viscosus) were measured from salivary samples. The performance of the diagnostic models was assessed by receiver operating characteristics (ROCs) and area under the ROC curve (AUC) analysis. The diagnostic models were constructed based on the subjects’ proteins and/or microbial profiles, resulting in two potential diagnosis models that achieved better diagnostic powers, with an AUC value > 0.750 for the diagnosis of Stages II, III, and IV periodontitis (Model PA-I; AUC: 0.796, sensitivity: 0.754, specificity: 0.712) and for the diagnosis of Stages III and IV periodontitis (Model PA-II; AUC: 0.796, sensitivity: 0.756, specificity: 0.868). This study can contribute to screening for periodontitis based on salivary biomarkers. MDPI 2020-10-14 /pmc/articles/PMC7602207/ /pubmed/33066545 http://dx.doi.org/10.3390/diagnostics10100820 Text en © 2020 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 Lee, Jungwon Lee, Jun-Beom Song, Hyun-Young Son, Min Jung Li, Ling Rhyu, In-Chul Lee, Yong-Moo Koo, Ki-Tae An, Jung-Sub Kim, Jin Sup Kim, Eunkyung Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva |
title | Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva |
title_full | Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva |
title_fullStr | Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva |
title_full_unstemmed | Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva |
title_short | Diagnostic Models for Screening of Periodontitis with Inflammatory Mediators and Microbial Profiles in Saliva |
title_sort | diagnostic models for screening of periodontitis with inflammatory mediators and microbial profiles in saliva |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602207/ https://www.ncbi.nlm.nih.gov/pubmed/33066545 http://dx.doi.org/10.3390/diagnostics10100820 |
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