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Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes

The rate of preterm birth is a public health concern worldwide because it is increasing and efforts to prevent it have failed. We report a Clinically Relevant Complex Systematic Review (CSCSR) designed to identify and evaluate the best available evidence in support of the association between periodo...

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Autores principales: Ramchandani, Manisha, Siddiqui, Muniza, Kanwar, Raveena, Lakha, Manwinder, Phi, Linda, Giacomelli, Luca, Chiappelli, Francesco
Formato: Texto
Lenguaje:English
Publicado: Biomedical Informatics 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3043352/
https://www.ncbi.nlm.nih.gov/pubmed/21364839
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author Ramchandani, Manisha
Siddiqui, Muniza
Kanwar, Raveena
Lakha, Manwinder
Phi, Linda
Giacomelli, Luca
Chiappelli, Francesco
author_facet Ramchandani, Manisha
Siddiqui, Muniza
Kanwar, Raveena
Lakha, Manwinder
Phi, Linda
Giacomelli, Luca
Chiappelli, Francesco
author_sort Ramchandani, Manisha
collection PubMed
description The rate of preterm birth is a public health concern worldwide because it is increasing and efforts to prevent it have failed. We report a Clinically Relevant Complex Systematic Review (CSCSR) designed to identify and evaluate the best available evidence in support of the association between periodontal status in women and pregnancy outcome of preterm low birth weight. We hypothesize that the traditional limits of research synthesis must be expanded to incorporate a translational component. As a proof-of-concept model, we propose that this CSCSR can yield greater validity of efficacy and effectiveness through supplementing its recommendations with data of the proteomic signature of periodontal disease in pregnancy, which can contribute to addressing specifically the predictive validity for adverse outcomes. For this CRCSR, systematic reviews were identified through The National Library of MedicinePubmed, The Cochrane library, CINAHL, Google Scholar, Web of Science, and the American Dental Association web library. Independent reviewers quantified the relevance and quality of this literature with R-AMSTAR. Homogeneity and inter-rater reliability testing were supplemented with acceptable sampling analysis. Research synthesis outcomes were analyzed qualitatively toward a Bayesian inference, and converge to demonstrate a definite association between maternal periodontal disease and pregnancy outcome. This CRCSR limits heterogeneity in terms of periodontal disease, outcome measure, selection bias, uncontrolled confounders and effect modifiers. Taken together, the translational CRCSR model we propose suggests that further research is advocated to explore the fundamental mechanisms underlying this association, from a molecular and proteomic perspective.
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spelling pubmed-30433522011-03-01 Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes Ramchandani, Manisha Siddiqui, Muniza Kanwar, Raveena Lakha, Manwinder Phi, Linda Giacomelli, Luca Chiappelli, Francesco Bioinformation Prediction Model The rate of preterm birth is a public health concern worldwide because it is increasing and efforts to prevent it have failed. We report a Clinically Relevant Complex Systematic Review (CSCSR) designed to identify and evaluate the best available evidence in support of the association between periodontal status in women and pregnancy outcome of preterm low birth weight. We hypothesize that the traditional limits of research synthesis must be expanded to incorporate a translational component. As a proof-of-concept model, we propose that this CSCSR can yield greater validity of efficacy and effectiveness through supplementing its recommendations with data of the proteomic signature of periodontal disease in pregnancy, which can contribute to addressing specifically the predictive validity for adverse outcomes. For this CRCSR, systematic reviews were identified through The National Library of MedicinePubmed, The Cochrane library, CINAHL, Google Scholar, Web of Science, and the American Dental Association web library. Independent reviewers quantified the relevance and quality of this literature with R-AMSTAR. Homogeneity and inter-rater reliability testing were supplemented with acceptable sampling analysis. Research synthesis outcomes were analyzed qualitatively toward a Bayesian inference, and converge to demonstrate a definite association between maternal periodontal disease and pregnancy outcome. This CRCSR limits heterogeneity in terms of periodontal disease, outcome measure, selection bias, uncontrolled confounders and effect modifiers. Taken together, the translational CRCSR model we propose suggests that further research is advocated to explore the fundamental mechanisms underlying this association, from a molecular and proteomic perspective. Biomedical Informatics 2011-01-06 /pmc/articles/PMC3043352/ /pubmed/21364839 Text en © 2010 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Prediction Model
Ramchandani, Manisha
Siddiqui, Muniza
Kanwar, Raveena
Lakha, Manwinder
Phi, Linda
Giacomelli, Luca
Chiappelli, Francesco
Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes
title Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes
title_full Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes
title_fullStr Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes
title_full_unstemmed Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes
title_short Proteomic signature of periodontal disease in pregnancy: Predictive validity for adverse outcomes
title_sort proteomic signature of periodontal disease in pregnancy: predictive validity for adverse outcomes
topic Prediction Model
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3043352/
https://www.ncbi.nlm.nih.gov/pubmed/21364839
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