Cargando…

Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients

We present the Danish Disease Trajectory Browser (DTB), a tool for exploring almost 25 years of data from the Danish National Patient Register. In the dataset comprising 7.2 million patients and 122 million admissions, users can identify diagnosis pairs with statistically significant directionality...

Descripción completa

Detalles Bibliográficos
Autores principales: Siggaard, Troels, Reguant, Roc, Jørgensen, Isabella F., Haue, Amalie D., Lademann, Mette, Aguayo-Orozco, Alejandro, Hjaltelin, Jessica X., Jensen, Anders Boeck, Banasik, Karina, Brunak, Søren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532164/
https://www.ncbi.nlm.nih.gov/pubmed/33009368
http://dx.doi.org/10.1038/s41467-020-18682-4
_version_ 1783589868342870016
author Siggaard, Troels
Reguant, Roc
Jørgensen, Isabella F.
Haue, Amalie D.
Lademann, Mette
Aguayo-Orozco, Alejandro
Hjaltelin, Jessica X.
Jensen, Anders Boeck
Banasik, Karina
Brunak, Søren
author_facet Siggaard, Troels
Reguant, Roc
Jørgensen, Isabella F.
Haue, Amalie D.
Lademann, Mette
Aguayo-Orozco, Alejandro
Hjaltelin, Jessica X.
Jensen, Anders Boeck
Banasik, Karina
Brunak, Søren
author_sort Siggaard, Troels
collection PubMed
description We present the Danish Disease Trajectory Browser (DTB), a tool for exploring almost 25 years of data from the Danish National Patient Register. In the dataset comprising 7.2 million patients and 122 million admissions, users can identify diagnosis pairs with statistically significant directionality and combine them to linear disease trajectories. Users can search for one or more disease codes (ICD-10 classification) and explore disease progression patterns via an array of functionalities. For example, a set of linear trajectories can be merged into a disease trajectory network displaying the entire multimorbidity spectrum of a disease in a single connected graph. Using data from the Danish Register for Causes of Death mortality is also included. The tool is disease-agnostic across both rare and common diseases and is showcased by exploring multimorbidity in Down syndrome (ICD-10 code Q90) and hypertension (ICD-10 code I10). Finally, we show how search results can be customized and exported from the browser in a format of choice (i.e. JSON, PNG, JPEG and CSV).
format Online
Article
Text
id pubmed-7532164
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-75321642020-10-19 Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients Siggaard, Troels Reguant, Roc Jørgensen, Isabella F. Haue, Amalie D. Lademann, Mette Aguayo-Orozco, Alejandro Hjaltelin, Jessica X. Jensen, Anders Boeck Banasik, Karina Brunak, Søren Nat Commun Article We present the Danish Disease Trajectory Browser (DTB), a tool for exploring almost 25 years of data from the Danish National Patient Register. In the dataset comprising 7.2 million patients and 122 million admissions, users can identify diagnosis pairs with statistically significant directionality and combine them to linear disease trajectories. Users can search for one or more disease codes (ICD-10 classification) and explore disease progression patterns via an array of functionalities. For example, a set of linear trajectories can be merged into a disease trajectory network displaying the entire multimorbidity spectrum of a disease in a single connected graph. Using data from the Danish Register for Causes of Death mortality is also included. The tool is disease-agnostic across both rare and common diseases and is showcased by exploring multimorbidity in Down syndrome (ICD-10 code Q90) and hypertension (ICD-10 code I10). Finally, we show how search results can be customized and exported from the browser in a format of choice (i.e. JSON, PNG, JPEG and CSV). Nature Publishing Group UK 2020-10-02 /pmc/articles/PMC7532164/ /pubmed/33009368 http://dx.doi.org/10.1038/s41467-020-18682-4 Text en © The Author(s) 2020 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Siggaard, Troels
Reguant, Roc
Jørgensen, Isabella F.
Haue, Amalie D.
Lademann, Mette
Aguayo-Orozco, Alejandro
Hjaltelin, Jessica X.
Jensen, Anders Boeck
Banasik, Karina
Brunak, Søren
Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients
title Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients
title_full Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients
title_fullStr Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients
title_full_unstemmed Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients
title_short Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients
title_sort disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million danish patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532164/
https://www.ncbi.nlm.nih.gov/pubmed/33009368
http://dx.doi.org/10.1038/s41467-020-18682-4
work_keys_str_mv AT siggaardtroels diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT reguantroc diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT jørgensenisabellaf diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT haueamalied diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT lademannmette diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT aguayoorozcoalejandro diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT hjaltelinjessicax diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT jensenandersboeck diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT banasikkarina diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients
AT brunaksøren diseasetrajectorybrowserforexploringtemporalpopulationwidediseaseprogressionpatternsin72milliondanishpatients