Evidence map›Paper›PMID 36151847›Full record

ArticleESC heart failure2023

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

Zehao Lin, Jiawei Zheng, Xiaochun Liu, Xiaojun Hu, Ren Fuxian, Dengfeng Gao

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
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  4. Management of hyperkalemia: Expert consensus from Kuwait - a Modified Delphi Approach.International journal of nephrology and renovascular disease · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Zehao LinDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, No. 157, Xiwu Rd, Xi'an, China.ORCID https://orcid.org/0000-0002-8941-5004
Jiawei ZhengDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, No. 157, Xiwu Rd, Xi'an, China.
Xiaochun LiuDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, No. 157, Xiwu Rd, Xi'an, China.
Xiaojun HuDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, No. 157, Xiwu Rd, Xi'an, China.
Ren FuxianDepartment of Cardiology, Meishan Branch of the Third Affiliated Hospital, Yan'an University School of Medicine, Meishan, Sichuan, China.
Dengfeng GaoDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, No. 157, Xiwu Rd, Xi'an, China.
Second Affiliated Hospital of Xi'an Jiaotong University · CNMeizhou City People's Hospital · CN

Funding

National Natural Science Foundation of China 81872563
6 · The paper itself

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.

Indexed as

Heart FailureHyperkalemiaHypokalemiaAgedAged, 80 and overCritical IllnessFemaleHumansMaleMiddle AgedPotassiumRetrospective StudiesPotassiumBlood potassium trajectoryGroup-based trajectory modelHeart failurePrognosis

Identifiers

PMID36151847
PMCPMC9871702
OpenAlexW4297174452

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.