dc.contributor.author | Özmen, Mahmut | en_US |
dc.contributor.author | Jabarulla, Mohamed Yaseen | en_US |
dc.contributor.author | Grabitz, Carl Robert | en_US |
dc.contributor.author | Melk, Anette | en_US |
dc.contributor.author | Wühl, Elke | en_US |
dc.contributor.author | Oeltze-Jafra, Steffen | en_US |
dc.contributor.editor | Gillmann, Christina | en_US |
dc.contributor.editor | Krone, Michael | en_US |
dc.contributor.editor | Lenti, Simone | en_US |
dc.date.accessioned | 2023-06-10T06:31:32Z | |
dc.date.available | 2023-06-10T06:31:32Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-3-03868-220-2 | |
dc.identifier.uri | https://doi.org/10.2312/evp.20231059 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/evp20231059 | |
dc.description.abstract | Pediatric chronic kidney disease (CKD) increases the risk of cardiovascular disease, stroke and other life-threatening conditions. Monitoring blood pressure in CKD patients is crucial to managing these risks. 24-hour ambulatory blood pressure monitoring (ABPM) is recommended for its comprehensive and accurate assessment of blood pressure over 24 hours. Analyzing and comparing 24-hour ABPM data of multiple diagnostic visits is a challenging task. Traditional methods involve comparing individual visits using paper printouts, which can be time-consuming and lacks a systematic overview of deviations over time. In this work, we present a dashboard visualization that allows clinicians (i) to assess the evolution of ABPM data over multiple diagnostic visits, (ii) to compare ABPM data of CKD patients with reference data of a healthy cohort, and (iii) to perform a detailed intra-individual comparison of the ABPM data acquired at two subsequent diagnostic visits. We demonstrate the dashboard in a case study of a patient with mild-to-moderate-stage CKD. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | CCS Concepts: Human-centered computing -> Visual analytics | |
dc.subject | Human centered computing | |
dc.subject | Visual analytics | |
dc.title | Comparative Visualization of Longitudinal 24-hour Ambulatory Blood Pressure Measurements in Pediatric Patients with Chronic Kidney Disease | en_US |
dc.description.seriesinformation | EuroVis 2023 - Posters | |
dc.identifier.doi | 10.2312/evp.20231059 | |
dc.identifier.pages | 25-27 | |
dc.identifier.pages | 3 pages | |