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

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          Abstract

          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).

          Abstract

          The Danish health system has been collecting health-related data on the entire Danish population for years. Here the authors present the Danish Disease Trajectory Browser (DTB), which allows users to explore population-wide disease progression patterns from data collected between 1994 and 2018.

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          Most cited references47

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          The Danish National Patient Registry: a review of content, data quality, and research potential

          Background The Danish National Patient Registry (DNPR) is one of the world’s oldest nationwide hospital registries and is used extensively for research. Many studies have validated algorithms for identifying health events in the DNPR, but the reports are fragmented and no overview exists. Objectives To review the content, data quality, and research potential of the DNPR. Methods We examined the setting, history, aims, content, and classification systems of the DNPR. We searched PubMed and the Danish Medical Journal to create a bibliography of validation studies. We included also studies that were referenced in retrieved papers or known to us beforehand. Methodological considerations related to DNPR data were reviewed. Results During 1977–2012, the DNPR registered 8,085,603 persons, accounting for 7,268,857 inpatient, 5,953,405 outpatient, and 5,097,300 emergency department contacts. The DNPR provides nationwide longitudinal registration of detailed administrative and clinical data. It has recorded information on all patients discharged from Danish nonpsychiatric hospitals since 1977 and on psychiatric inpatients and emergency department and outpatient specialty clinic contacts since 1995. For each patient contact, one primary and optional secondary diagnoses are recorded according to the International Classification of Diseases. The DNPR provides a data source to identify diseases, examinations, certain in-hospital medical treatments, and surgical procedures. Long-term temporal trends in hospitalization and treatment rates can be studied. The positive predictive values of diseases and treatments vary widely (<15%–100%). The DNPR data are linkable at the patient level with data from other Danish administrative registries, clinical registries, randomized controlled trials, population surveys, and epidemiologic field studies – enabling researchers to reconstruct individual life and health trajectories for an entire population. Conclusion The DNPR is a valuable tool for epidemiological research. However, both its strengths and limitations must be considered when interpreting research results, and continuous validation of its clinical data is essential.
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            Network medicine: a network-based approach to human disease.

            Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.
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              Epidemiology and aetiology of heart failure.

              Heart failure (HF) is a rapidly growing public health issue with an estimated prevalence of >37.7 million individuals globally. HF is a shared chronic phase of cardiac functional impairment secondary to many aetiologies, and patients with HF experience numerous symptoms that affect their quality of life, including dyspnoea, fatigue, poor exercise tolerance, and fluid retention. Although the underlying causes of HF vary according to sex, age, ethnicity, comorbidities, and environment, the majority of cases remain preventable. HF is associated with increased morbidity and mortality, and confers a substantial burden to the health-care system. HF is a leading cause of hospitalization among adults and the elderly. In the USA, the total medical costs for patients with HF are expected to rise from US$20.9 billion in 2012 to $53.1 billion by 2030. Improvements in the medical management of risk factors and HF have stabilized the incidence of this disease in many countries. In this Review, we provide an overview of the latest epidemiological data on HF, and propose future directions for reducing the ever-increasing HF burden.

                Author and article information

                Contributors
                soren.brunak@cpr.ku.dk
                Journal
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                2 October 2020
                2 October 2020
                2020
                : 11
                : 4952
                Affiliations
                [1 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, , University of Copenhagen, ; DK-2200 Copenhagen, Denmark
                [2 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Institute for Next Generation Healthcare, , Icahn School of Medicine at Mount Sinai, ; New York, NY 10029-6574 USA
                Author information
                http://orcid.org/0000-0002-0350-3899
                http://orcid.org/0000-0001-7656-7976
                http://orcid.org/0000-0003-1828-223X
                http://orcid.org/0000-0003-2489-2499
                http://orcid.org/0000-0003-0316-5866
                Article
                18682
                10.1038/s41467-020-18682-4
                7532164
                33009368
                faf05a78-57b3-4105-ae2c-04985380a3aa
                © 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/.

                History
                : 17 April 2020
                : 1 September 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100009708, Novo Nordisk Fonden (Novo Nordisk Foundation);
                Award ID: NNF14CC0001
                Award ID: NNF17OC0027594
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                computational platforms and environments,software,diseases,signs and symptoms
                Uncategorized
                computational platforms and environments, software, diseases, signs and symptoms

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