Evidence mapPaperPMID 42445561Full record

ArticleInternational journal of general medicine2026

Metabolic Endotypes for Dialysis Risk Stratification in Chronic Kidney Disease Stages G2-G4: A Pragmatic Cluster Analysis Using Routine Laboratory Tests.

Li Guo, Peng Shu, Dan Qin, Wei Jiang, Fang Xu, Ting Wang, Xingruo Zeng, Jun Li

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Article in International journal of general medicine, 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

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8 authors.

Li Guo *Department of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.
Peng Shu *Department of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.ORCID 0000-0001-8945-8402
Dan QinDepartment of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.
Wei JiangDepartment of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.
Fang XuDepartment of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.
Ting WangDepartment of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.
Xingruo ZengDepartment of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.
Jun LiDepartment of nephrology, The Central Hospital of Wuhan, Hubei, Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Chronic kidney disease (CKD) affects over 850 million people globally, but traditional staging based on eGFR and albuminuria fails to capture metabolic heterogeneity and divergent outcomes in CKD stages G2-G4 (15 < eGFR < 90 mL/min/1.73m Methods: This single-center retrospective cohort study included 400 CKD stages G2-G4 patients (2022-2024) from The Central Hospital of Wuhan. Nine routine biomarkers (estimated glomerular filtration rate [eGFR], uric acid, glucose, phosphate, parathyroid hormone [PTH], albumin, hemoglobin, D-dimer, total cholesterol) underwent robust preprocessing, followed by unsupervised K-means clustering. The nine input variables were selected a priori based on their established roles in core CKD pathophysiological pathways (CKD‑MBD, malnutrition‑inflammation‑anemia, and glycolipid‑uric acid dysregulation), grounding the clustering in biological mechanisms rather than purely empirical data‑driven reduction. Optimal clusters (K=4) were confirmed via multiple statistical metrics and clinical interpretability. Results: Four distinct metabolic endotypes emerged: 1) Inflammatory-hypercoagulable (high D-dimer, low albumin); 2) Severe CKD-MBD-anemia (lowest eGFR/hemoglobin, highest PTH); 3) Metabolically favorable (highest eGFR/albumin/hemoglobin, lowest D-dimer); 4) Glycolipid-uric acid dysregulation (high glucose/uric acid/phosphate). Dialysis rates differed drastically: 59.4% (Endotype 2), 46.7% (Endotype 4), 38.7% (Endotype 1), and 6.7% (Endotype 3) (all P<0.001). Multivariable logistic regression incorporating metabolic endotype, age, gender, and eGFR yielded a corrected AUC of 0.838 (95% CI: 0.763-0.915) for predicting dialysis initiation, with a sensitivity of 94.6% and specificity of 69.4%. Conclusion: This pragmatic approach, based on routinely available laboratory tests, suggests potential application value for risk stratification in clinical practice and provides a preliminary framework for future precision medicine research. However, given the single‑center retrospective design, its generalizability requires external validation in large‑scale prospective multi‑center cohorts before clinical implementation.

Indexed as

chronic kidney diseasedialysis initiationk-means unsupervised clusteringmetabolic endotyperisk stratificationroutine laboratory biomarkers

Identifiers

PMID42445561
PMCPMC13361786

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