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Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients
Blood potassium concentration ([K(+)]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K(+)] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K(+)] varies significantly during the therap...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309791/ https://www.ncbi.nlm.nih.gov/pubmed/28198403 http://dx.doi.org/10.1038/srep42492 |
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author | Corsi, Cristiana Cortesi, Marilisa Callisesi, Giulia De Bie, Johan Napolitano, Carlo Santoro, Antonio Mortara, David Severi, Stefano |
author_facet | Corsi, Cristiana Cortesi, Marilisa Callisesi, Giulia De Bie, Johan Napolitano, Carlo Santoro, Antonio Mortara, David Severi, Stefano |
author_sort | Corsi, Cristiana |
collection | PubMed |
description | Blood potassium concentration ([K(+)]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K(+)] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K(+)] varies significantly during the therapy. To elucidate the mechanism linking [K(+)] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K(+)] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (T(S/A)) was used as starting point for an ECG-based [K(+)] estimate (K(ECG)). Leave-one-out cross-validation was performed. Agreement between K(ECG) and reference [K(+)] from blood samples was promising (error: −0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of K(ECG) correlation to blood [K(+)]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia. |
format | Online Article Text |
id | pubmed-5309791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53097912017-02-22 Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients Corsi, Cristiana Cortesi, Marilisa Callisesi, Giulia De Bie, Johan Napolitano, Carlo Santoro, Antonio Mortara, David Severi, Stefano Sci Rep Article Blood potassium concentration ([K(+)]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K(+)] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K(+)] varies significantly during the therapy. To elucidate the mechanism linking [K(+)] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K(+)] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (T(S/A)) was used as starting point for an ECG-based [K(+)] estimate (K(ECG)). Leave-one-out cross-validation was performed. Agreement between K(ECG) and reference [K(+)] from blood samples was promising (error: −0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of K(ECG) correlation to blood [K(+)]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia. Nature Publishing Group 2017-02-15 /pmc/articles/PMC5309791/ /pubmed/28198403 http://dx.doi.org/10.1038/srep42492 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Corsi, Cristiana Cortesi, Marilisa Callisesi, Giulia De Bie, Johan Napolitano, Carlo Santoro, Antonio Mortara, David Severi, Stefano Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients |
title | Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients |
title_full | Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients |
title_fullStr | Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients |
title_full_unstemmed | Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients |
title_short | Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients |
title_sort | noninvasive quantification of blood potassium concentration from ecg in hemodialysis patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309791/ https://www.ncbi.nlm.nih.gov/pubmed/28198403 http://dx.doi.org/10.1038/srep42492 |
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