Evidence map›Paper›PMID 40881126›Full record

ArticleFrontiers in endocrinology2025

Aggregate index of systemic inflammation as a novel prognostic biomarker in Chinese patients with acute decompensated heart failure: a population-based real-world study.

Lin Hu, Yangjie Deng, Chuanjin Liu, Yinghao Kuang, Xinfang Huang, Jinyan Zhang, Wanfen Huang, Yafei Jian, Guobo Xie, Yang Zou and 1 more

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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

11 authors.

Lin HuDepartment of Cardiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Yangjie DengDepartment of Cardiology, Yongfeng County Hospital of Traditional Chinese Medicine, Jian, Jiangxi, China.
Chuanjin LiuDepartment of Cardiology, Yongfeng County Hospital of Traditional Chinese Medicine, Jian, Jiangxi, China.
Yinghao KuangJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Xinfang HuangJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Jinyan ZhangJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Wanfen HuangJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Yafei JianJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Guobo XieDepartment of Cardiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Yang ZouJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Shuhua ZhangJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Inflammation is hypothesized as an early trigger for decompensation in heart failure patients. This study aims to evaluate the prognostic value of a novel inflammatory biomarker, the Aggregate Index of Systemic Inflammation (AISI), for predicting 30-day mortality in patients with acute decompensated heart failure (ADHF). Methods: This analysis included 2,765 patients from the Jiangxi-ADHF II registry (2018-2024). Complete blood counts were measured at hospital admission, with 30-day mortality outcomes followed. Multivariable Cox proportional hazards model was employed to analyze the association between AISI and all-cause mortality. Results: During 30-day follow-up, the overall mortality rate was 7.34% (203 deaths), with rates progressively increasing across AISI quartiles (Q1-Q4: 2.32%, 3.33%, 5.21%, 18.50%). Compared with the lowest AISI quartile, the highest quartile was associated with a 210% higher risk of 30-day mortality (Hazard Ratio: 3.10, 1.62-5.94). This association remained robust across multiple sensitivity analyses, including subgroup analysis, temporal sensitivity assessments, and data integrity verification. Further spline regression analysis revealed a U-shaped curve association between AISI (and LnAISI) and 30-day mortality in ADHF patients (P for non-linearity < 0.05). In general, both extremely low and high levels of AISI and its natural logarithm (LnAISI) were associated with an increased risk of 30-day mortality in ADHF patients. Moreover, in predicting 30-day mortality among ADHF patients, the AISI demonstrated significantly superior predictive value compared to white blood cell count, neutrophil count, monocyte count, and lymphocyte count (Area under the curve=0.77; all DeLong tests P <0.05), with an optimal threshold of 925.44. Discussion: This population-based retrospective cohort study demonstrated the predictive value of AISI for short-term outcomes in Chinese ADHF patients. Compared to conventional inflammatory biomarkers, AISI significantly improved the predictive performance for 30-day mortality in ADHF patients. These findings may facilitate optimized prevention of adverse outcomes in ADHF and enable early risk stratification through targeted assessment of individual ADHF patients.

Indexed as

Heart FailureInflammationAcute DiseaseAgedAged, 80 and overBiomarkersChinaEast Asian PeopleFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisRegistriesBiomarkersacute decompensated heart failureaggregate index of systemic inflammationChineseinflammationrisk stratificationrisk stratification inflammation

Identifiers

PMID40881126
PMCPMC12380547

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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.