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ORIGINAL RESEARCH article

Front. Med.

Sec. Nephrology

Volume 12 - 2025 | doi: 10.3389/fmed.2025.1469363

This article is part of the Research Topic Enhancing Kidney Transplant Outcomes through Machine Learning Innovations View all articles

Risk Prediction of Kidney Function in Long-term Kidney Transplant Recipients

Provisionally accepted
Krzysztof Batko Krzysztof Batko 1Anna Sączek Anna Sączek 1Małgorzata Banaszkiewicz Małgorzata Banaszkiewicz 1Jolanta Malyszko Jolanta Malyszko 2Ewa Koc-Zorawska Ewa Koc-Zorawska 3Marcin J Zorawski Marcin J Zorawski 3Katarzyna Siek Katarzyna Siek 1Karolina Niezabitowska Karolina Niezabitowska 1Marcin Krzanowski Marcin Krzanowski 1Alina Bętkowska-Prokop Alina Bętkowska-Prokop 1Andrzej Kraśniak Andrzej Kraśniak 1Katarzyna Krzanowska Katarzyna Krzanowska 1*
  • 1 Jagiellonian University Medical College, Kraków, Poland
  • 2 Medical University of Warsaw, Warsaw, Masovian, Poland
  • 3 Medical University of Bialystok, Bialystok, Podlaskie Voivodeship, Poland

The final, formatted version of the article will be published soon.

    Background: Limited tools exist for predicting kidney function in long-term kidney transplant recipients (KTRs). Elabela, apelin and the APJ receptor constitute an axis that regulates vascular and cardiac physiology in opposition to the renin-angiotensin-aldosterone system. Methods: Longitudinal, observational cohort of 102 KTRs who maintained graft function for at least 24 months, with no acute rejection history or active infection upon presentation. Serum apelin, elabela, fibroblast growth factor 23 (FGF-23) and α Klotho were tested using enzyme-linked immunoassay and compared with a control group of 32 healthy controls (HCs).Results: When comparing with HCs, higher serum FGF-23 (P<0.01), elabela (P<0.01) and apelin (P=0.04), but lower α Klotho (P=0.02) concentrations were observed in long-term KTRs. Most KTRs had stable trajectories of renal function. Mean estimated glomerular filtration (eGFR) over 2-year follow-up was associated with significantly lower odds of graft loss (OR 0.04, 95% CI 0.01-0.15; p<0.001). Baseline renal function was significantly correlated with mineral-bone markers (log[FGF-

    Keywords: Kidney, Elabela, Apelin, risk prediction, machine learning, Transplantation

    Received: 23 Jul 2024; Accepted: 24 Feb 2025.

    Copyright: © 2025 Batko, Sączek, Banaszkiewicz, Malyszko, Koc-Zorawska, Zorawski, Siek, Niezabitowska, Krzanowski, Bętkowska-Prokop, Kraśniak and Krzanowska. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Katarzyna Krzanowska, Jagiellonian University Medical College, Kraków, Poland

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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