Evidence map›Paper›PMID 40708738›Full record

ArticleWorld journal of emergency medicine2025

A risk prediction model for acute kidney injury following acute heart failure in an emergency department cohort in China.

Lingjie Cao, Yuanyuan Pei, Xiaolu Ma, Liping Guo, Fengtao Yang, Fange Shi, Pengfei Wang, Dilu Li, Kunyu Yang, Jihong Zhu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in World journal of emergency medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Lingjie Cao1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Yuanyuan Pei1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Xiaolu Ma1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Liping Guo1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Fengtao Yang1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Fange Shi1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Pengfei Wang2Emergency Department, Beijing Friendship Hospital, Capital Medical University, Beijing 100044, China.
Dilu Li1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Kunyu Yang1Emergency Department, Peking University People's Hospital, Beijing 100044, China.
Jihong Zhu1Emergency Department, Peking University People's Hospital, Beijing 100044, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) is a severe and fatal complication of acute heart failure (AHF). Existing studies on AKI following AHF in the Chinese population have scarce insights available from the emergency department (ED). This study aimed to investigate the predictive factors of patients with AHF complicated with AKI in a Chinese ED cohort, and to establish a risk prediction model.

methodsHospitalized patients diagnosed with AHF in the ED from December 2016 to September 2023 were included. The overall dataset were divided into the training set and the testing set at a 7:3 ratio. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for AKI in patients with AHF in the training set, leading to the development of a risk prediction model. The performance of the model was further assessed.

resultsA total of 789 patients with AHF were enrolled, with an AKI incidence of 29.7%. The mortality rates of the AKI and non-AKI groups were 23.1% and 7.6%, respectively. Logistic regression analysis showed that the levels of white blood cell (

conclusionThis risk prediction model might assist physician to predict AKI following AHF effectively in the emergency setting.

Indexed as

Acute heart failureAcute kidney injuryPredictive modelRisk factor

Identifiers

PMID40708738
PMCPMC12283460

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