Evidence map›Paper›PMID 41608439›Full record

ArticleFrontiers in medicine2025

High systemic immune inflammation index values are associated with prolonged length of hospital stay in patients with acute exacerbation of chronic obstructive pulmonary disease: a retrospective cohort study.

Jiming Xiao, Yunqiu Liu, Liying Zheng, Qing Yang, Xinxin Hao, Yibo Zhao, Dongmei Chen, Baojing Feng, Liye Wang

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Jiming XiaoKailuan General Hospital Affiliated to North China University of Science and Technology, Tangshan, China.
Yunqiu LiuDepartment of Pulmonary and Critical Care Medicine, Kailuan General Hospital, Tangshan, China.
Liying ZhengDepartment of Pulmonary and Critical Care Medicine, Kailuan General Hospital, Tangshan, China.
Qing YangDepartment of Pulmonary and Critical Care Medicine, Kailuan General Hospital, Tangshan, China.
Xinxin HaoKailuan General Hospital Affiliated to North China University of Science and Technology, Tangshan, China.
Yibo ZhaoKailuan General Hospital Affiliated to North China University of Science and Technology, Tangshan, China.
Dongmei ChenKailuan General Hospital Affiliated to North China University of Science and Technology, Tangshan, China.
Baojing FengDepartment of Pulmonary and Critical Care Medicine, Kailuan General Hospital, Tangshan, China.
Liye WangDepartment of Pulmonary and Critical Care Medicine, Kailuan General Hospital, Tangshan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to investigate the association between the Systemic Immune Inflammation Index (SII) and the prolonged length of hospital stay (PLOS) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods: A retrospective analysis was conducted involving 986 patients aged ≥ 40 years with AECOPD admitted to Kailuan General Hospital between January 2018 and December 2024. PLOS was defined as a stay exceeding 7 days. Complete blood counts were collected within 24 h of admission to calculate the SII, which was the log-transformed and denoted as In-SII. Logistic regression analysis was employed to compare the predictive value of In-SII and In-NLR (neutrophil-to-lymphocyte ratio) for PLOS in patients with AECOPD. Additionally, restricted cubic splines (RCS) and decision curves analysis (DCA) were utilized to explore the nonlinear relationship and clinical net benefit between In-SII and PLOS in patients with AECOPD. Results: In-SII was an independent risk factor for PLOS in patients with AECOPD (odds ratios for Model 1, Model 2, and Model 3 were 1.527, 1.294, and 1.496, respectively; Conclusion: High SII serves as an independent risk factor for PLOS in patients with AECOPD. This indicated that patients with AECOPD exhibiting high SII levels have poorer outcomes, necessitating earlier implementation of more robust intervention measures and close monitoring of disease progression.

Indexed as

acute exacerbationchronic obstructive pulmonary diseaseprolonged length of hospital stayretrospective cohort studySystemic Immune Inflammation Index

Identifiers

PMID41608439
PMCPMC12834773

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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.