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GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study
by
Musiał, Kinga
, Bargenda-Lange, Agnieszka
, Stojanowski, Jakub
, Gołębiowski, Tomasz
in
Accuracy
/ Adolescent
/ Artificial Intelligence
/ Biomarkers - blood
/ Cardiovascular disease
/ Child
/ Child, Preschool
/ Children
/ Chronic kidney failure
/ Development and progression
/ Diabetes
/ Disease Progression
/ Diseases
/ Enzyme-linked immunosorbent assay
/ Epidermal growth factor
/ Epidermal Growth Factor - blood
/ Female
/ Growth Differentiation Factor 15 - blood
/ Humans
/ Immunity (Disease)
/ Inflammation
/ Kidney diseases
/ Male
/ Medical research
/ Medicine, Experimental
/ Mortality
/ Neopterin - blood
/ Neural Networks, Computer
/ Patients
/ Pediatrics
/ Pilot Projects
/ Renal Insufficiency, Chronic - blood
/ Renal Insufficiency, Chronic - diagnosis
/ Renal Insufficiency, Chronic - pathology
2025
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GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study
by
Musiał, Kinga
, Bargenda-Lange, Agnieszka
, Stojanowski, Jakub
, Gołębiowski, Tomasz
in
Accuracy
/ Adolescent
/ Artificial Intelligence
/ Biomarkers - blood
/ Cardiovascular disease
/ Child
/ Child, Preschool
/ Children
/ Chronic kidney failure
/ Development and progression
/ Diabetes
/ Disease Progression
/ Diseases
/ Enzyme-linked immunosorbent assay
/ Epidermal growth factor
/ Epidermal Growth Factor - blood
/ Female
/ Growth Differentiation Factor 15 - blood
/ Humans
/ Immunity (Disease)
/ Inflammation
/ Kidney diseases
/ Male
/ Medical research
/ Medicine, Experimental
/ Mortality
/ Neopterin - blood
/ Neural Networks, Computer
/ Patients
/ Pediatrics
/ Pilot Projects
/ Renal Insufficiency, Chronic - blood
/ Renal Insufficiency, Chronic - diagnosis
/ Renal Insufficiency, Chronic - pathology
2025
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GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study
by
Musiał, Kinga
, Bargenda-Lange, Agnieszka
, Stojanowski, Jakub
, Gołębiowski, Tomasz
in
Accuracy
/ Adolescent
/ Artificial Intelligence
/ Biomarkers - blood
/ Cardiovascular disease
/ Child
/ Child, Preschool
/ Children
/ Chronic kidney failure
/ Development and progression
/ Diabetes
/ Disease Progression
/ Diseases
/ Enzyme-linked immunosorbent assay
/ Epidermal growth factor
/ Epidermal Growth Factor - blood
/ Female
/ Growth Differentiation Factor 15 - blood
/ Humans
/ Immunity (Disease)
/ Inflammation
/ Kidney diseases
/ Male
/ Medical research
/ Medicine, Experimental
/ Mortality
/ Neopterin - blood
/ Neural Networks, Computer
/ Patients
/ Pediatrics
/ Pilot Projects
/ Renal Insufficiency, Chronic - blood
/ Renal Insufficiency, Chronic - diagnosis
/ Renal Insufficiency, Chronic - pathology
2025
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GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study
Journal Article
GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools—A Pilot Study
2025
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Overview
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.
Publisher
MDPI AG,MDPI
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