ArticleESC heart failure2023
Assessing potassium levels in critically ill patients with heart failure: application of a group-based trajectory model.
Article in ESC heart failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 8 citations in OpenAlex.
- Impact of postoperative serum potassium levels and variability on 1-year mortality rate in coronary artery bypass grafting patients: a retrospective cohort study.Journal of cardiothoracic surgery · 2026Article
- Early arterial lactate trajectories and mortality risk in critically ill heart failure: a two-cohort trajectory analysis.Scientific reports · 2025Article
- Association of longitudinal blood urea nitrogen trajectory with in-hospital and 28-day mortality in acute heart failure with cardiorenal syndrome.European journal of medical research · 2025Article
- Management of hyperkalemia: Expert consensus from Kuwait - a Modified Delphi Approach.International journal of nephrology and renovascular disease · 2024Article
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- Understanding the viral shedding time of Omicron variant BA.2 infection in Shanghai: A population-based observational study.Heliyon · 2023Article
- Assessing potassium levels in critically ill patients with heart failure: application of a group-based trajectory model.ESC heart failure · 2023Article
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6 authors at 2 institutions in 1 country.
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Abstract
aimsAbnormalities 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
resultsA 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.
conclusionsCritically 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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