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Historical overview of development in methods to estimate burden of disease due to congenital disorders

Congenital disorders (often also called birth defects) are an important cause of mortality and disability. They encompass a wide range of disorders with differing severity that can affect any aspect of structure or function. Understanding their epidemiology is important in developing appropriate ser...

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Detalles Bibliográficos
Autores principales: Modell, Bernadette, Darlison, Matthew W, Lawn, Joy E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167262/
https://www.ncbi.nlm.nih.gov/pubmed/30209753
http://dx.doi.org/10.1007/s12687-018-0382-4
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author Modell, Bernadette
Darlison, Matthew W
Lawn, Joy E
author_facet Modell, Bernadette
Darlison, Matthew W
Lawn, Joy E
author_sort Modell, Bernadette
collection PubMed
description Congenital disorders (often also called birth defects) are an important cause of mortality and disability. They encompass a wide range of disorders with differing severity that can affect any aspect of structure or function. Understanding their epidemiology is important in developing appropriate services both for their prevention and treatment. The need for epidemiological data on congenital disorders has been recognised for many decades. Here, we provide a historical overview of work that has led to the development of the Modell Global Database of Congenital Disorders (MGDb)—a tool that can be used to generate evidence-based country, regional and global estimates of the birth prevalence and outcomes of congenital disorders.
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spelling pubmed-61672622018-10-12 Historical overview of development in methods to estimate burden of disease due to congenital disorders Modell, Bernadette Darlison, Matthew W Lawn, Joy E J Community Genet Original Article Congenital disorders (often also called birth defects) are an important cause of mortality and disability. They encompass a wide range of disorders with differing severity that can affect any aspect of structure or function. Understanding their epidemiology is important in developing appropriate services both for their prevention and treatment. The need for epidemiological data on congenital disorders has been recognised for many decades. Here, we provide a historical overview of work that has led to the development of the Modell Global Database of Congenital Disorders (MGDb)—a tool that can be used to generate evidence-based country, regional and global estimates of the birth prevalence and outcomes of congenital disorders. Springer Berlin Heidelberg 2018-09-12 2018-10 /pmc/articles/PMC6167262/ /pubmed/30209753 http://dx.doi.org/10.1007/s12687-018-0382-4 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Modell, Bernadette
Darlison, Matthew W
Lawn, Joy E
Historical overview of development in methods to estimate burden of disease due to congenital disorders
title Historical overview of development in methods to estimate burden of disease due to congenital disorders
title_full Historical overview of development in methods to estimate burden of disease due to congenital disorders
title_fullStr Historical overview of development in methods to estimate burden of disease due to congenital disorders
title_full_unstemmed Historical overview of development in methods to estimate burden of disease due to congenital disorders
title_short Historical overview of development in methods to estimate burden of disease due to congenital disorders
title_sort historical overview of development in methods to estimate burden of disease due to congenital disorders
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167262/
https://www.ncbi.nlm.nih.gov/pubmed/30209753
http://dx.doi.org/10.1007/s12687-018-0382-4
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