Evidence map›Paper›PMID 40076962›Full record

ArticleInternational journal of molecular sciences2025

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

Kinga Musiał, Jakub Stojanowski, Agnieszka Bargenda-Lange, Tomasz Gołębiowski

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kinga MusiałDepartment of Pediatric Nephrology, Wrocław Medical University, Borowska 213, 50-556 Wrocław, Poland.ORCID 0000-0002-9000-7585
Jakub StojanowskiDepartment of Nephrology and Transplantation Medicine, Wrocław Medical University, Borowska 213, 50-556 Wrocław, Poland.ORCID 0000-0002-0527-2190
Agnieszka Bargenda-LangeDepartment of Pediatric Nephrology, Wrocław Medical University, Borowska 213, 50-556 Wrocław, Poland.
Tomasz GołębiowskiDepartment of Nephrology and Transplantation Medicine, Wrocław Medical University, Borowska 213, 50-556 Wrocław, Poland.ORCID 0000-0001-5477-2020

Funding

Wroclaw Medical University SUB.C210.19.045
6 · The paper itself

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.

Indexed as

Artificial IntelligenceEpidermal Growth FactorGrowth Differentiation Factor 15NeopterinRenal Insufficiency, ChronicAdolescentBiomarkersChildChild, PreschoolDisease ProgressionFemaleHumansMaleNeural Networks, ComputerPilot ProjectsBiomarkersEpidermal Growth FactorGDF15 protein, humanGrowth Differentiation Factor 15Neopterinartificial intelligencechronic inflammationepidermal growth factorgrowth differentiation factor 15leave-one-out cross-validation (LOOCV) methodmultilayer perceptron (MLP) network model

Identifiers

PMID40076962
PMCPMC11899747

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.