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Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model

AIMS: Abnormalities in potassium homeostasis are frequently seen in hospitalized patients. A poor outcome in heart failure (HF) has been linked to both hypokalaemia and hyperkalaemia. The studies on the connection between variations in potassium levels and all‐cause mortality remain scarce. We delin...

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Autores principales: Lin, Zehao, Zheng, Jiawei, Liu, Xiaochun, Hu, Xiaojun, Fuxian, Ren, Gao, Dengfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871702/
https://www.ncbi.nlm.nih.gov/pubmed/36151847
http://dx.doi.org/10.1002/ehf2.14161
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author Lin, Zehao
Zheng, Jiawei
Liu, Xiaochun
Hu, Xiaojun
Fuxian, Ren
Gao, Dengfeng
author_facet Lin, Zehao
Zheng, Jiawei
Liu, Xiaochun
Hu, Xiaojun
Fuxian, Ren
Gao, Dengfeng
author_sort Lin, Zehao
collection PubMed
description AIMS: Abnormalities in potassium homeostasis are frequently seen in hospitalized patients. A poor outcome in heart failure (HF) has been linked to both hypokalaemia and hyperkalaemia. The studies on the connection between variations in potassium levels and all‐cause mortality remain scarce. We delineated trajectories of potassium levels and investigated the association of these trajectories with all‐cause mortality of critically ill patients with HF. METHODS AND RESULTS: A retrospective analysis of blood potassium levels (9 times) in patients with HF after being admitted to the intensive care unit (ICU). Potassium levels were divided into three groups according to the first serum potassium level in ICU and thereafter categorized as follows: hypokalaemia group (n = 336) (<3.5 mmol/L), normal blood potassium‐level group (n = 3322) (3.5–5.0 mmol/L), and hyperkalaemia group (n = 395) (>5.0 mmol/L). According to the group‐based trajectory modelling (GBTM), the hyperkalaemia group and the normal blood potassium‐level group can be divided into three trajectory groups: the low‐level stable group, the medium‐level stable group, and the high‐level decline group. The hypokalaemia group can be divided into two trajectory groups: the low‐level rise group and the high‐level rise group. A total of 4053 HF patients were included (mean age 71.81 ± 13.12 years, 54.90% males, 45.10% females). After adjusting for possible confounding variables, in the hyperkalaemia group, the low‐level stable group had lower 28 day [high‐level decline group vs. low‐level stable group hazard ratio (HR), 95% confidence interval (CI): 2.917, 1.555–5.473; P < 0.05] and 365 day (high‐level decline group vs. low‐level stable group HR, 95% CI: 2.854, 1.820–4.475; P < 0.05) all‐cause mortality. In the normal blood potassium‐level group, the medium‐level stable group had lower 28 day (medium‐level stable group vs. low‐level stable group HR, 95% CI: 0.776, 0.657–0.918; P < 0.05) and 365 day (medium‐level stable group vs. low‐level stable group HR, 95% CI: 0.827, 0.733–0.934; P < 0.05) all‐cause mortality. In the hypokalaemia group, the cumulative survival of the high‐level rise group and the low‐level rise group did not differ significantly. CONCLUSIONS: Critically ill patients with HF have blood potassium trajectories. And the trajectories are associated with all‐cause mortality for hyperkalaemia and normal blood potassium‐level patients. GBTM is a granular method to describe the evolution of blood potassium, which may increase the current knowledge of blood potassium‐level adjustment.
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spelling pubmed-98717022023-01-25 Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model Lin, Zehao Zheng, Jiawei Liu, Xiaochun Hu, Xiaojun Fuxian, Ren Gao, Dengfeng ESC Heart Fail Original Articles AIMS: Abnormalities in potassium homeostasis are frequently seen in hospitalized patients. A poor outcome in heart failure (HF) has been linked to both hypokalaemia and hyperkalaemia. The studies on the connection between variations in potassium levels and all‐cause mortality remain scarce. We delineated trajectories of potassium levels and investigated the association of these trajectories with all‐cause mortality of critically ill patients with HF. METHODS AND RESULTS: A retrospective analysis of blood potassium levels (9 times) in patients with HF after being admitted to the intensive care unit (ICU). Potassium levels were divided into three groups according to the first serum potassium level in ICU and thereafter categorized as follows: hypokalaemia group (n = 336) (<3.5 mmol/L), normal blood potassium‐level group (n = 3322) (3.5–5.0 mmol/L), and hyperkalaemia group (n = 395) (>5.0 mmol/L). According to the group‐based trajectory modelling (GBTM), the hyperkalaemia group and the normal blood potassium‐level group can be divided into three trajectory groups: the low‐level stable group, the medium‐level stable group, and the high‐level decline group. The hypokalaemia group can be divided into two trajectory groups: the low‐level rise group and the high‐level rise group. A total of 4053 HF patients were included (mean age 71.81 ± 13.12 years, 54.90% males, 45.10% females). After adjusting for possible confounding variables, in the hyperkalaemia group, the low‐level stable group had lower 28 day [high‐level decline group vs. low‐level stable group hazard ratio (HR), 95% confidence interval (CI): 2.917, 1.555–5.473; P < 0.05] and 365 day (high‐level decline group vs. low‐level stable group HR, 95% CI: 2.854, 1.820–4.475; P < 0.05) all‐cause mortality. In the normal blood potassium‐level group, the medium‐level stable group had lower 28 day (medium‐level stable group vs. low‐level stable group HR, 95% CI: 0.776, 0.657–0.918; P < 0.05) and 365 day (medium‐level stable group vs. low‐level stable group HR, 95% CI: 0.827, 0.733–0.934; P < 0.05) all‐cause mortality. In the hypokalaemia group, the cumulative survival of the high‐level rise group and the low‐level rise group did not differ significantly. CONCLUSIONS: Critically ill patients with HF have blood potassium trajectories. And the trajectories are associated with all‐cause mortality for hyperkalaemia and normal blood potassium‐level patients. GBTM is a granular method to describe the evolution of blood potassium, which may increase the current knowledge of blood potassium‐level adjustment. John Wiley and Sons Inc. 2022-09-24 /pmc/articles/PMC9871702/ /pubmed/36151847 http://dx.doi.org/10.1002/ehf2.14161 Text en © 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Lin, Zehao
Zheng, Jiawei
Liu, Xiaochun
Hu, Xiaojun
Fuxian, Ren
Gao, Dengfeng
Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model
title Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model
title_full Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model
title_fullStr Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model
title_full_unstemmed Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model
title_short Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model
title_sort assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871702/
https://www.ncbi.nlm.nih.gov/pubmed/36151847
http://dx.doi.org/10.1002/ehf2.14161
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