Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200, Copenhagen, Denmark.
Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, NY, 10029-6574, USA.
Nat Commun. 2020 Oct 2;11(1):4952. doi: 10.1038/s41467-020-18682-4.
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).
我们展示了丹麦疾病轨迹浏览器（DTB），这是一种用于探索丹麦国家患者登记处近 25 年数据的工具。在包含 720 万患者和 1.22 亿次入院的数据集，用户可以识别具有统计学意义的方向性的诊断对，并将它们组合成线性疾病轨迹。用户可以搜索一个或多个疾病代码（ICD-10 分类），并通过一系列功能探索疾病进展模式。例如，一组线性轨迹可以合并成一个疾病轨迹网络，在单个连通图中显示疾病的整个多种疾病谱。使用来自丹麦死因登记处的数据，还包括死亡率信息。该工具在罕见和常见疾病方面都是无病种的，通过探索唐氏综合征（ICD-10 代码 Q90）和高血压（ICD-10 代码 I10）的多种疾病情况来展示。最后，我们展示了如何自定义搜索结果并以用户选择的格式（即 JSON、PNG、JPEG 和 CSV）从浏览器中导出。
