ArticleScientific reports2022
Potential progression biomarkers of diabetic kidney disease determined using comprehensive machine learning analysis of non-targeted metabolomics.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
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The trial behind it
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Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.
- Pooled it
- Metabolomics approaches for the early detection and therapeutics: type 2 diabetes-induced diabetic kidney disease-a systematic review and meta-analysis.Metabolomics : Official journal of the Metabolomic Society · 2025Pooled it
- Biomarkers in Diabetic Kidney Disease: Early Detection, Prognostic Assessment, and Integration with Multi-Omics Signatures.Life (Basel, Switzerland) · 2026Review
- The Need for Omics Studies in Chronic Kidney Disease of Unknown Etiology (CKDu): A Narrative Review and Perspective.International journal of molecular sciences · 2026Review
- Observational
- SGLT2 Inhibitor-Associated Changes in Urinary Volatile Organic Compounds in Diabetic Kidney Disease: A Comprehensive Study.Nephrology (Carlton, Vic.) · 2026Article
- Akkermansia muciniphila Delays the Progression of Diabetic Nephropathy by Reducing the Accumulation of Uremic Toxins in the Feces and Peripheral BloodEndocrine, metabolic & immune disorders drug targets · 2026Article
- Pathogenic variants prevalence patients with diabetic kidney disease in Japan: A descriptive study.Journal of diabetes investigation · 2025Article
- Detection of Fast Decliner of Diabetic Kidney Disease Using Chiral Amino Acid Profiling: A Pilot Study.Chemistry & biodiversity · 2025Article
- The Omics-Driven Machine Learning Path to Cost-Effective Precision Medicine in Chronic Kidney Disease.Proteomics · 2025Review
- Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques.Scientific reports · 2025Article
- Metabolomics profiling in multi-ancestral individuals with type 2 diabetes in Singapore identified metabolites associated with renal function decline.Diabetologia · 2025Article
- Predicting rapid decline in kidney function among type 2 diabetes patients: A machine learning approach.Heliyon · 2025Article
- Advancements in the non-invasive diagnosis of renal fibrosis.Frontiers in medicine · 2025Review
- From bytes to nephrons: AI's journey in diabetic kidney disease.Journal of nephrology · 2025Review
- Steps to understanding diabetes kidney disease: a focus on metabolomics.The Korean journal of internal medicine · 2024Review
- Metabolomics in diabetic nephropathy: Unveiling novel biomarkers for diagnosis (Review).Molecular medicine reports · 2024Review
- Intervention treatment reducing cellular senescence inhibits tubulointerstitial fibrosis in diabetic mice following acute kidney injury.Clinical science (London, England : 1979) · 2024Article
- Kidney tea [Frontiers in pharmacology · 2024Article
- CKD Urine Metabolomics: Modern Concepts and Approaches.Pathophysiology : the official journal of the International Society for Pathophysiology · 2023Review
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic kidney disease is the main cause of end-stage renal disease worldwide. The prediction of the clinical course of patients with diabetic kidney disease remains difficult, despite the identification of potential biomarkers; therefore, novel biomarkers are needed to predict the progression of the disease. We conducted non-targeted metabolomics using plasma and urine of patients with diabetic kidney disease whose estimated glomerular filtration rate was between 30 and 60 mL/min/1.73 m
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Registered trials
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