Assessing potassium levels in critically ill patients with heart failure: application of a group‐based trajectory model. (24th September 2022)

• Record Type: Journal Article
• Authors: Lin, Zehao; Zheng, Jiawei; Liu, Xiaochun; Hu, Xiaojun; Fuxian, Ren; Gao, Dengfeng
• Is Part Of: ESC heart failure. Volume 10:Number 1(2023)
• Page Start: 57
• Page End: 65
• Publication Date: 2022-09-24
• Subjects: Blood potassium trajectory -- Heart failure -- Group‐based trajectory model -- Prognosis; Heart failure -- Periodicals; 616.129005
• DOI: 10.1002/ehf2.14161
• Languages: English
• ISSNs: 2055-5822

Abstract

Abstract: 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.