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Network-medicine framework for studying disease trajectories in U.S. veterans

A better understanding of the sequential and temporal aspects in which diseases occur in patient’s lives is essential for developing improved intervention strategies that reduce burden and increase the quality of health services. Here we present a network-based framework to study disease relationshi...

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Autores principales: do Valle, Italo Faria, Ferolito, Brian, Gerlovin, Hanna, Costa, Lauren, Demissie, Serkalem, Linares, Franciel, Cohen, Jeremy, Gagnon, David R., Gaziano, J. Michael, Begoli, Edmon, Cho, Kelly, Barabási, Albert-László
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283486/
https://www.ncbi.nlm.nih.gov/pubmed/35835798
http://dx.doi.org/10.1038/s41598-022-15764-9
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author do Valle, Italo Faria
Ferolito, Brian
Gerlovin, Hanna
Costa, Lauren
Demissie, Serkalem
Linares, Franciel
Cohen, Jeremy
Gagnon, David R.
Gaziano, J. Michael
Begoli, Edmon
Cho, Kelly
Barabási, Albert-László
author_facet do Valle, Italo Faria
Ferolito, Brian
Gerlovin, Hanna
Costa, Lauren
Demissie, Serkalem
Linares, Franciel
Cohen, Jeremy
Gagnon, David R.
Gaziano, J. Michael
Begoli, Edmon
Cho, Kelly
Barabási, Albert-László
author_sort do Valle, Italo Faria
collection PubMed
description A better understanding of the sequential and temporal aspects in which diseases occur in patient’s lives is essential for developing improved intervention strategies that reduce burden and increase the quality of health services. Here we present a network-based framework to study disease relationships using Electronic Health Records from > 9 million patients in the United States Veterans Health Administration (VHA) system. We create the Temporal Disease Network, which maps the sequential aspects of disease co-occurrence among patients and demonstrate that network properties reflect clinical aspects of the respective diseases. We use the Temporal Disease Network to identify disease groups that reflect patterns of disease co-occurrence and the flow of patients among diagnoses. Finally, we define a strategy for the identification of trajectories that lead from one disease to another. The framework presented here has the potential to offer new insights for disease treatment and prevention in large health care systems.
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spelling pubmed-92834862022-07-16 Network-medicine framework for studying disease trajectories in U.S. veterans do Valle, Italo Faria Ferolito, Brian Gerlovin, Hanna Costa, Lauren Demissie, Serkalem Linares, Franciel Cohen, Jeremy Gagnon, David R. Gaziano, J. Michael Begoli, Edmon Cho, Kelly Barabási, Albert-László Sci Rep Article A better understanding of the sequential and temporal aspects in which diseases occur in patient’s lives is essential for developing improved intervention strategies that reduce burden and increase the quality of health services. Here we present a network-based framework to study disease relationships using Electronic Health Records from > 9 million patients in the United States Veterans Health Administration (VHA) system. We create the Temporal Disease Network, which maps the sequential aspects of disease co-occurrence among patients and demonstrate that network properties reflect clinical aspects of the respective diseases. We use the Temporal Disease Network to identify disease groups that reflect patterns of disease co-occurrence and the flow of patients among diagnoses. Finally, we define a strategy for the identification of trajectories that lead from one disease to another. The framework presented here has the potential to offer new insights for disease treatment and prevention in large health care systems. Nature Publishing Group UK 2022-07-14 /pmc/articles/PMC9283486/ /pubmed/35835798 http://dx.doi.org/10.1038/s41598-022-15764-9 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
do Valle, Italo Faria
Ferolito, Brian
Gerlovin, Hanna
Costa, Lauren
Demissie, Serkalem
Linares, Franciel
Cohen, Jeremy
Gagnon, David R.
Gaziano, J. Michael
Begoli, Edmon
Cho, Kelly
Barabási, Albert-László
Network-medicine framework for studying disease trajectories in U.S. veterans
title Network-medicine framework for studying disease trajectories in U.S. veterans
title_full Network-medicine framework for studying disease trajectories in U.S. veterans
title_fullStr Network-medicine framework for studying disease trajectories in U.S. veterans
title_full_unstemmed Network-medicine framework for studying disease trajectories in U.S. veterans
title_short Network-medicine framework for studying disease trajectories in U.S. veterans
title_sort network-medicine framework for studying disease trajectories in u.s. veterans
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283486/
https://www.ncbi.nlm.nih.gov/pubmed/35835798
http://dx.doi.org/10.1038/s41598-022-15764-9
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