Evidence map›Paper›PMID 38824546›Full record

Observational studyBMC emergency medicine2024

The impact of hyperkalemia on ICU admission and mortality: a retrospective study of Chinese emergency department data.

Jian Sun, Qingyuan Liu, Samuel Seery, Lu Sun, Yuan Yuan, Wenwen Wang, Yan Wang, Ziwei Cui, Yueguo Wang, Yulan Wang and 4 more

Abstract readObservational Study
In one paragraph

Observational study in BMC emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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

14 authors.

Jian Sun *Department of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Qingyuan Liu *School of Mathematics and Physics, Anhui Jianzhu University, Hefei, Anhui, 230009, China.
Samuel Seery *School of Mathematical Sciences, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, 230026, China.
Lu Sun *Department of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Yuan YuanDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Wenwen WangDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Yan WangDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Ziwei CuiDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Yueguo WangDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Yulan WangDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Jiashan ZhuDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Mengping ZhangSchool of Mathematical Sciences, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, 230026, China. mpzhang@ustc.edu.cn.
Yinglei LaiSchool of Mathematical Sciences, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, 230026, China. laiyinglei@ustc.edu.cn.
Kui JinDepartment of Emergency Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, 230001, China. kuijin@ustc.edu.cn.

Funding

Anhui Major Science and Technology Project 2020b07050001National Natural Science Foundation of China (National Science Foundation of China) 12126604R&D project of Pazhou Lab (Huangpu) 2023K0609
6 · The paper itself

Abstract

objectiveThis study assesses the influence of hyperkalemia on both disease severity and the risk of mortality among patients admitted to the emergency room.

methodsThis retrospective observational study utilized data from the Chinese Emergency Triage Assessment and Treatment database (CETAT, version 2.0), which was designed to evaluate and optimize management strategies for emergency room (ER) patients. Patients were systematically categorized based on serum potassium levels. Relationships between serum potassium levels, risk of mortality, and the severity of illness were then analyzed using multifactorial logistic regression and through Receiver Operating Characteristic (ROC) analysis. The effectiveness of various treatments at lowering potassium levels was also investigated.

results12,799 emergency patients were enrolled, of whom 20.1% (n = 2,577) were hypokalemic and 2.98% (n = 381) were hyperkalemic. Among hyperkalemic patients, the leading reasons for visiting the ER were altered consciousness 23.88% (n = 91), cardiovascular symptoms 22.31% (n = 85), and gastrointestinal symptoms 20.47% (n = 78). Comparative analysis with patients exhibiting normal potassium levels revealed hyperkalemia as an independent factor associated with mortality in the ER. Mortality risk appears to positively correlate with increasing potassium levels, reaching peaks when blood potassium levels ranged between 6.5 and 7.0. Hyperkalemia emerged as a strong predictor of death in the ER, with an Area Under the Curve (AUC) of 0.89. The most frequently prescribed treatment for hyperkalemia patients was diuretics (57.32%, n = 188), followed by intravenous sodium bicarbonate (50.91%, n = 167), IV calcium (37.2%, n = 122), insulin combined with high glucose (27.74%, n = 91), and Continuous Renal Replacement Therapy (CRRT) for 19.82% (n = 65). Among these, CRRT appeared to be the most efficacious at reducing potassium levels. Diuretics appeared relatively ineffective, while high-glucose insulin, sodium bicarbonate, and calcium preparations having no significant effect on the rate of potassium decline.

conclusionHyperkalemia is common in emergency situations, especially among patients with altered consciousness. There is a strong positive correlation between the severity of hyperkalemia and mortality risk. CRRT appears to be the most effective potassium reducting strategy, while the use of diuretics should be approached with caution.

Indexed as

Emergency Service, HospitalHyperkalemiaIntensive Care UnitsAdultAgedChinaFemaleHospital MortalityHumansMaleMiddle AgedPatient AdmissionPotassiumRetrospective StudiesROC CurveSeverity of Illness IndexPotassiumDisease severityEmergency roomHyperkalemiaMortality risk

Identifiers

PMID38824546
PMCPMC11144311

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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.