GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study

Cell-mediated immunity and chronic inflammation are hallmarks of chronic kidney disease (CKD). Growth differentiation factor 15 (GDF15) is a marker of inflammation and an integrative signal in stress conditions. Epidermal growth factor (EGF) is a tubule-specific protein that modulates the regeneration of injured renal tubules. Neopterin is a product of activated monocytes and macrophages and serves as a marker of cell-mediated immunity. Our aim was to assess the role of the above-mentioned parameters in the progression of CKD in children using artificial intelligence tools. The study group consisted of 151 children with CKD stages 1-5. EGF, GDF15, and neopterin serum concentrations were assessed by ELISA. The patients' anthropometric data, biochemical parameters, EGF, GDF15, and neopterin serum values were implemented into the artificial neural network (ANN). The most precise model contained EGF, GDF15, and neopterin as input parameters and classified patients into either CKD 1-3 or CKD 4-5 groups with an excellent accuracy of 96.77%. The presented AI model, with serum concentrations of EGF, GDF15, and neopterin as input parameters, may serve as a useful predictor of CKD progression. It suggests the essential role of inflammatory processes in the renal function decline in the course of CKD in children.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-03-06
DOI
https://doi.org/10.3390/ijms26052344
Citations
1
Primary Topic
GDF15 and Related Biomarkers
Type
article
Field-Weighted Citation Impact
1.67

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article

GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study

Kinga Musiał, Jakub Stojanowski, Tomasz Gołębiowski, Agnieszka Bargenda-Lange
1 citations
International Journal of Molecular Sciences
GDF15 and Related Biomarkers
1.67
article

GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study

Kinga Musiał, Jakub Stojanowski, Tomasz Gołębiowski, Agnieszka Bargenda-Lange
article en
1 citations

Abstract

Cell-mediated immunity and chronic inflammation are hallmarks of chronic kidney disease (CKD). Growth differentiation factor 15 (GDF15) is a marker of inflammation and an integrative signal in stress conditions. Epidermal growth factor (EGF) is a tubule-specific protein that modulates the regeneration of injured renal tubules. Neopterin is a product of activated monocytes and macrophages and serves as a marker of cell-mediated immunity. Our aim was to assess the role of the above-mentioned parameters in the progression of CKD in children using artificial intelligence tools. The study group consisted of 151 children with CKD stages 1-5. EGF, GDF15, and neopterin serum concentrations were assessed by ELISA. The patients' anthropometric data, biochemical parameters, EGF, GDF15, and neopterin serum values were implemented into the artificial neural network (ANN). The most precise model contained EGF, GDF15, and neopterin as input parameters and classified patients into either CKD 1-3 or CKD 4-5 groups with an excellent accuracy of 96.77%. The presented AI model, with serum concentrations of EGF, GDF15, and neopterin as input parameters, may serve as a useful predictor of CKD progression. It suggests the essential role of inflammatory processes in the renal function decline in the course of CKD in children.

International Journal of Molecular SciencesVol. 26(5)
Wroclaw Medical University (PL)
Uniwersytet Medyczny im. Piastów Slaskich we Wroclawiu
Openalex Percentile: Top 20%
GDF15 and Related Biomarkers
1.67
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