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Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol

INTRODUCTION: Family history (FH) is an important part of the patients’ medical history during preventive management at model family medicine practices (MFMP). It currently includes a one (or two) generational inquiry, predominately in terms of cardiovascular diseases, arterial hypertension, and dia...

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Autores principales: Selič, Polona, Klemenc-Ketiš, Zalika, Zelko, Erika, Kravos, Andrej, Rifel, Janez, Makivić, Irena, Poplas Susič, Antonija, Tevžič, Špela, Cerovič, Metka, Peterlin, Borut, Kopčavar Guček, Nena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7478082/
https://www.ncbi.nlm.nih.gov/pubmed/32952700
http://dx.doi.org/10.2478/sjph-2020-0004
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author Selič, Polona
Klemenc-Ketiš, Zalika
Zelko, Erika
Kravos, Andrej
Rifel, Janez
Makivić, Irena
Poplas Susič, Antonija
Tevžič, Špela
Cerovič, Metka
Peterlin, Borut
Kopčavar Guček, Nena
author_facet Selič, Polona
Klemenc-Ketiš, Zalika
Zelko, Erika
Kravos, Andrej
Rifel, Janez
Makivić, Irena
Poplas Susič, Antonija
Tevžič, Špela
Cerovič, Metka
Peterlin, Borut
Kopčavar Guček, Nena
author_sort Selič, Polona
collection PubMed
description INTRODUCTION: Family history (FH) is an important part of the patients’ medical history during preventive management at model family medicine practices (MFMP). It currently includes a one (or two) generational inquiry, predominately in terms of cardiovascular diseases, arterial hypertension, and diabetes, but not of other diseases with a probable genetic aetiology. Beside family history, no application-based algorithm is available to determine the risk level for specific chronic diseases in Slovenia. METHODS: A web application-based algorithm aimed at determining the risk level for selected monogenic and polygenic diseases will be developed. The data will be collected in MFMP; approximately 40 overall with a sample including healthy preventive examination attendees (approximately 1,000). Demographic data, a three-generational FH, a medical history of acquired and congenital risk factors for the selected diseases, and other important clinical factors will be documented. RESULTS: The results will be validated by a clinical genetic approach based on family pedigrees and the next-generation genetic sequencing method. After the risk of genetic diseases in the Slovenian population has been determined, clinical pathways for acting according to the assessed risk level will be prepared. CONCLUSION: By means of a public health tool providing an assessment of family predisposition, a contribution to the effective identification of people at increased risk of the selected monogenic and polygenic diseases is expected, lessening a significant public health burden.
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spelling pubmed-74780822020-12-13 Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol Selič, Polona Klemenc-Ketiš, Zalika Zelko, Erika Kravos, Andrej Rifel, Janez Makivić, Irena Poplas Susič, Antonija Tevžič, Špela Cerovič, Metka Peterlin, Borut Kopčavar Guček, Nena Zdr Varst Original Scientific Article INTRODUCTION: Family history (FH) is an important part of the patients’ medical history during preventive management at model family medicine practices (MFMP). It currently includes a one (or two) generational inquiry, predominately in terms of cardiovascular diseases, arterial hypertension, and diabetes, but not of other diseases with a probable genetic aetiology. Beside family history, no application-based algorithm is available to determine the risk level for specific chronic diseases in Slovenia. METHODS: A web application-based algorithm aimed at determining the risk level for selected monogenic and polygenic diseases will be developed. The data will be collected in MFMP; approximately 40 overall with a sample including healthy preventive examination attendees (approximately 1,000). Demographic data, a three-generational FH, a medical history of acquired and congenital risk factors for the selected diseases, and other important clinical factors will be documented. RESULTS: The results will be validated by a clinical genetic approach based on family pedigrees and the next-generation genetic sequencing method. After the risk of genetic diseases in the Slovenian population has been determined, clinical pathways for acting according to the assessed risk level will be prepared. CONCLUSION: By means of a public health tool providing an assessment of family predisposition, a contribution to the effective identification of people at increased risk of the selected monogenic and polygenic diseases is expected, lessening a significant public health burden. Sciendo 2020-12-13 /pmc/articles/PMC7478082/ /pubmed/32952700 http://dx.doi.org/10.2478/sjph-2020-0004 Text en © 2020 Polona Selič et al., published by Sciendo http://creativecommons.org/licenses/by-nc-nd/3.0 This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Original Scientific Article
Selič, Polona
Klemenc-Ketiš, Zalika
Zelko, Erika
Kravos, Andrej
Rifel, Janez
Makivić, Irena
Poplas Susič, Antonija
Tevžič, Špela
Cerovič, Metka
Peterlin, Borut
Kopčavar Guček, Nena
Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol
title Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol
title_full Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol
title_fullStr Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol
title_full_unstemmed Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol
title_short Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level – A New Tool for Primary Prevention: A Study Protocol
title_sort development of an algorithm for determining of genetic risk at the primary healthcare level – a new tool for primary prevention: a study protocol
topic Original Scientific Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7478082/
https://www.ncbi.nlm.nih.gov/pubmed/32952700
http://dx.doi.org/10.2478/sjph-2020-0004
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