Evidence map›Paper›PMID 40761379›Full record

ArticleJournal of inflammation research2025

The Clinical Value of Systemic Immune Inflammatory Index in Predicting the Prognosis of Patients with Bloodstream Infection.

Shuheng Ou, Hong Lu, Rui Qu, Xiaolong Cui, Zhou Xiong, Fangfang Fan, Xiao Yu, Chaolu Hasi

Abstract read
In one paragraph

Article in Journal of inflammation research, 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

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. Observational
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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

8 authors.

Shuheng Ou *Academy of Medical Sciences, Shanxi Medical University School, Taiyuan, People's Republic of China.
Hong Lu *Department of Laboratory Medicine, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Rui QuFirst Clinical Medical College, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Xiaolong CuiFirst Clinical Medical College, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Zhou XiongSchool of Public Health, Anhui Medical University, Hefei, People's Republic of China.
Fangfang FanNHC Key Laboratory of pneumoconiosis, Shanxi Key Laboratory of respiratory diseases, Department of pulmonary and critical care medicine, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Xiao YuNHC Key Laboratory of pneumoconiosis, Shanxi Key Laboratory of respiratory diseases, Department of pulmonary and critical care medicine, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Chaolu HasiDepartment of Laboratory Medicine, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: We analyzed the correlation between systemic immune inflammatory index (SII), systemic inflammatory response index (SIRI), systemic inflammatory index (AISI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and mortality in patients with bloodstream infection to determine their application potential in predicting the prognosis of bloodstream infection. Methods: We calculated SII, SIRI, AISI, NLR, PLR, and MLR in 469 patients with bloodstream infections. Logistic regression modeling, generalized additive modeling (GAM), and smoothed curve fitting were used to investigate the correlation of SII and other inflammatory markers with mortality in patients with bloodstream infections. Area under the curve (AUC) of ROC was used to assess the predictive effect of SII and other inflammatory markers. Results: Levels of SII, SIRI, AISI, NLR, PLR, and MLR were significantly higher in the mortality group of this study (P < 0.05). There were significant differences in gender, age, diabetes, cardiovascular disease, respiratory disease, NEUT and LUMPH between the survival group and the death group (p < 0.05). Smooth curve fitting and GAM showed that SII and NLR had a non-linear relationship with death. After adjustment, the breakpoints (K) were 1711 and 7.22, respectively (P < 0.05), and there was a positive correlation on both sides of the breakpoint. The comparison of AUC values showed that SII and NLR had higher accuracy in predicting the risk of death in patients with bloodstream infection. Conclusion: Studies demonstrates that SII and NLR are more predictive of mortality risk in patients with bloodstream infections. Patients with diabetes, cardiovascular disease, or respiratory disease should be monitored regularly for SII and NLR indicators to reduce the risk of death.

Indexed as

bloodstream infectionneutrophil-to-lymphocyte ratioprognosissmooth curve fittingsystemic immune inflammatory index

Identifiers

PMID40761379
PMCPMC12318860

What Socratic holds

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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 Socratic graph.