Association between the nutritional inflammation index and mortality among patients with sepsis: insights from traditional methods and machine learning-based mortality prediction

ANLR is a robust and independent predictor of sepsis-related mortality, outperforming conventional biomarkers. Incorporating ANLR into routine clinical workflows could improve risk assessment and facilitate individualized treatment strategies for patients with severe sepsis. Further prospective studies are needed to validate these findings and explore potential therapeutic implications.

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Publication Details

Journal
BMC Infectious Diseases
Published
2025-08-14
DOI
https://doi.org/10.1186/s12879-025-11429-w
Citations
1
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.35
Controls
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article

Association between the nutritional inflammation index and mortality among patients with sepsis: insights from traditional methods and machine learning-based mortality prediction

Yuanshuo Ge, Hu Ding, Cheng Zhang, Zhe Wang
1 citations
BMC Infectious Diseases
Sepsis Diagnosis and Treatment
1.35
article

Association between the nutritional inflammation index and mortality among patients with sepsis: insights from traditional methods and machine learning-based mortality prediction

Yuanshuo Ge, Hu Ding, Cheng Zhang, Zhe Wang
article en
1 citations

Abstract

ANLR is a robust and independent predictor of sepsis-related mortality, outperforming conventional biomarkers. Incorporating ANLR into routine clinical workflows could improve risk assessment and facilitate individualized treatment strategies for patients with severe sepsis. Further prospective studies are needed to validate these findings and explore potential therapeutic implications.

BMC Infectious DiseasesVol. 25(1)
General Hospital of Shenyang Military Region (CN), Jinzhou Medical University (CN)
Openalex Percentile: Top 17%
Sepsis Diagnosis and Treatment
1.35
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Association between the nutritional inflammation index and mortality among patients with sepsis: insights from traditional methods and machine learning-based mortality prediction — Yuanshuo Ge, Hu Ding, et al. · BMC Infectious Diseases (2025) | TGRS Research Map | TGRS