Evidence mapPaperPMID 42445793Full record

ArticleFrontiers in nutrition2026

Nutritional-inflammatory-metabolic indices associated with in-hospital mortality in acute kidney injury patients undergoing continuous renal replacement therapy: dose-response analysis and machine learning-based risk stratification.

Yingying Cao, Guangxin Gu, Ruiwen Wang, Jiuxu Bai, Zhe Hao, Bin Wang, Ting Yang, Yu Wang, Yan Zhang

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Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Yingying CaoDepartment of Blood Purification, General Hospital of Northern Theater Command, Shenyang, China.
Guangxin GuKey Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University, Shenyang, China.
Ruiwen WangKey Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University, Shenyang, China.
Jiuxu BaiDepartment of Blood Purification, General Hospital of Northern Theater Command, Shenyang, China.
Zhe HaoDepartment of Blood Purification, General Hospital of Northern Theater Command, Shenyang, China.
Bin WangDepartment of Blood Purification, General Hospital of Northern Theater Command, Shenyang, China.
Ting YangDepartment of Blood Purification, General Hospital of Northern Theater Command, Shenyang, China.
Yu WangDepartment of Orthopedics, General Hospital of Northern Theater Command, Shenyang, China.
Yan ZhangDepartment of Blood Purification, General Hospital of Northern Theater Command, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Composite indices derived from routine laboratory parameters can reflect nutritional, inflammatory, and metabolic status, yet their prognostic value in acute kidney injury (AKI) patients receiving continuous renal replacement therapy (CRRT) has not been systematically compared. This study aimed to evaluate and compare the prognostic value of six such indices and to integrate them into machine learning-based prediction models. Methods: This retrospective cohort study enrolled 1,732 AKI patients who received CRRT between 2020 and 2025. Six composite indices-Albumin-to-Alkaline Phosphatase Ratio (AAPR), Prognostic Nutritional Index (PNI), Albumin-Bilirubin Score (ALBI), Blood Urea Nitrogen to Creatinine Ratio (BUN/Cr), Systemic Immune-Inflammation Index (SII), and Neutrophil-to-Lymphocyte Ratio (NLR)-were calculated from laboratory data within the first 24 h of ICU admission. Associations with in-hospital mortality were evaluated using multivariable Cox regression, restricted cubic spline (RCS) analysis, and subgroup analyses. Feature selection and six machine learning models with SHAP interpretability analysis were employed for risk prediction. Results: A total of 507 patients (29.3%) died during hospitalization. AAPR was the only index with a consistent protective association in the fully adjusted model (Q4 vs. Q1: HR 0.683, 95% CI 0.524-0.890; Conclusion: Among six nutritional-inflammatory-metabolic composite indices, AAPR showed the most robust prognostic value, with an L-shaped dose-response relationship identifying 0.203 as a risk stratification threshold. The U-shaped association of PNI cautions against equating higher values with better prognosis.

Indexed as

acute kidney injuryAlbumin-to-Alkaline Phosphatase Ratio (AAPR)continuous renal replacement therapy (CRRT)dose–response analysisin-hospital mortalitymachine learning

Identifiers

PMID42445793
PMCPMC13359152

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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.