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<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>doi:10.23919/CinC49843.2019.9005904</dc:identifier><dc:language>eng</dc:language><dc:creator>Palmieri, F.</dc:creator><dc:creator>Ramírez, J.</dc:creator><dc:creator>Laguna, P.</dc:creator><dc:creator>Gomis, P.</dc:creator><dc:creator>Ferreira, D.</dc:creator><dc:creator>Ruiz, J.E.</dc:creator><dc:creator>Bergasa, B.</dc:creator><dc:creator>Martín-Yebra, A.</dc:creator><dc:creator>Bukhari, H.A.</dc:creator><dc:creator>Pueyo, E.</dc:creator><dc:creator>Martínez, J.P.</dc:creator><dc:title>T-Wave Morphology Changes as Surrogate for Blood Potassium Concentration in Hemodialysis Patients</dc:title><dc:identifier>ART-2019-122005</dc:identifier><dc:description>End-stage renal disease (ESRD) patients undergoing hemodialysis (HD) are at high risk of arrhythmias and sudden cardiac death as a result of blood potassium concentration ([K+ ]) changes. The aim of this study is to investigate if dw, a time-warping-based electrocardiogram (ECG) biomarker of T-wave morphology changes, reflects [K+] evolution in HD patients, facilitating noninvasive [K+] monitoring and avoiding in-hospital blood tests analysis. 48-hour ECGs and a set of hourly-collected blood samples from 12 ESRD patients were acquired and analyzed. dw was calculated between a reference T-wave, measured at the end of the HD session, and the T-waves corresponding to each hour along the whole HD session, when [K+] was measured from blood samples. The values of dw correlated with the relative variations in [K+] with respect to the reference value (end of HD, ¿[K+ ]), with a median (interquartile) correlation coefficient of 0.90 (0.30), evidencing a strong relation between them. Our findings support the use of dw as a surrogate of ¿[K+], suggesting a potential use of dw for non-invasive hyperkalemia monitoring both in hospital and ambulatory settings.</dc:description><dc:date>2019</dc:date><dc:source>http://zaguan.unizar.es/record/98287</dc:source><dc:doi>10.23919/CinC49843.2019.9005904</dc:doi><dc:identifier>http://zaguan.unizar.es/record/98287</dc:identifier><dc:identifier>oai:zaguan.unizar.es:98287</dc:identifier><dc:relation>info:eu-repo/grantAgreement/ES/DGA-FEDER/T39-17R-BSICoS</dc:relation><dc:relation>info:eu-repo/grantAgreement/EUR/ERC-2014-StG-638284</dc:relation><dc:relation>info:eu-repo/grantAgreement/EC/H2020/786833/EU/GENetics and the Electrocardiogram for predicting Scd rISk/GENESIS</dc:relation><dc:relation>This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 786833-GENESIS</dc:relation><dc:relation>info:eu-repo/grantAgreement/ES/MINECO-FEDER/DPI2016-75458-R</dc:relation><dc:identifier.citation>Computing in Cardiology 46 (2019), [4 pp]</dc:identifier.citation><dc:rights>by</dc:rights><dc:rights>http://creativecommons.org/licenses/by/3.0/es/</dc:rights><dc:rights>info:eu-repo/semantics/openAccess</dc:rights></dc:dc>

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