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Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier

Background: Low-grade inflammation is a significant component of chronic kidney disease (CKD). Systemic immune inflammation index (SII), a newly defined ratio combining neutrophil, lymphocyte, and platelet counts, has not yet been evaluated in the pediatric CKD population nor in the context of CKD p...

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Autores principales: Kawalec, Anna, Stojanowski, Jakub, Mazurkiewicz, Paulina, Choma, Anna, Gaik, Magdalena, Pluta, Mateusz, Szymański, Michał, Bruciak, Aleksandra, Gołębiowski, Tomasz, Musiał, Kinga
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647735/
https://www.ncbi.nlm.nih.gov/pubmed/37959376
http://dx.doi.org/10.3390/jcm12216911
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author Kawalec, Anna
Stojanowski, Jakub
Mazurkiewicz, Paulina
Choma, Anna
Gaik, Magdalena
Pluta, Mateusz
Szymański, Michał
Bruciak, Aleksandra
Gołębiowski, Tomasz
Musiał, Kinga
author_facet Kawalec, Anna
Stojanowski, Jakub
Mazurkiewicz, Paulina
Choma, Anna
Gaik, Magdalena
Pluta, Mateusz
Szymański, Michał
Bruciak, Aleksandra
Gołębiowski, Tomasz
Musiał, Kinga
author_sort Kawalec, Anna
collection PubMed
description Background: Low-grade inflammation is a significant component of chronic kidney disease (CKD). Systemic immune inflammation index (SII), a newly defined ratio combining neutrophil, lymphocyte, and platelet counts, has not yet been evaluated in the pediatric CKD population nor in the context of CKD progression or dialysis. Thus, this study aimed to analyze the complete blood cell count (CBC)-driven parameters, including SII, in children with CKD and to assess their potential usefulness in the prediction of the need for chronic dialysis. Methods: A single-center, retrospective study was conducted on 27 predialysis children with CKD stages 4–5 and 39 children on chronic dialysis. The data were analyzed with the artificial intelligence tools. Results: The Random Forest Classifier (RFC) model with the input variables of neutrophil count, mean platelet volume (MPV), and SII turned out to be the best predictor of the progression of pediatric CKD into end-stage kidney disease (ESKD) requiring dialysis. Out of these variables, SII showed the largest share in the prediction of the need for renal replacement therapy. Conclusions: Chronic inflammation plays a pivotal role in the progression of CKD into ESKD. Among CBC-driven ratios, SII seems to be the most useful predictor of the need for chronic dialysis in CKD children.
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spelling pubmed-106477352023-11-03 Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier Kawalec, Anna Stojanowski, Jakub Mazurkiewicz, Paulina Choma, Anna Gaik, Magdalena Pluta, Mateusz Szymański, Michał Bruciak, Aleksandra Gołębiowski, Tomasz Musiał, Kinga J Clin Med Article Background: Low-grade inflammation is a significant component of chronic kidney disease (CKD). Systemic immune inflammation index (SII), a newly defined ratio combining neutrophil, lymphocyte, and platelet counts, has not yet been evaluated in the pediatric CKD population nor in the context of CKD progression or dialysis. Thus, this study aimed to analyze the complete blood cell count (CBC)-driven parameters, including SII, in children with CKD and to assess their potential usefulness in the prediction of the need for chronic dialysis. Methods: A single-center, retrospective study was conducted on 27 predialysis children with CKD stages 4–5 and 39 children on chronic dialysis. The data were analyzed with the artificial intelligence tools. Results: The Random Forest Classifier (RFC) model with the input variables of neutrophil count, mean platelet volume (MPV), and SII turned out to be the best predictor of the progression of pediatric CKD into end-stage kidney disease (ESKD) requiring dialysis. Out of these variables, SII showed the largest share in the prediction of the need for renal replacement therapy. Conclusions: Chronic inflammation plays a pivotal role in the progression of CKD into ESKD. Among CBC-driven ratios, SII seems to be the most useful predictor of the need for chronic dialysis in CKD children. MDPI 2023-11-03 /pmc/articles/PMC10647735/ /pubmed/37959376 http://dx.doi.org/10.3390/jcm12216911 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kawalec, Anna
Stojanowski, Jakub
Mazurkiewicz, Paulina
Choma, Anna
Gaik, Magdalena
Pluta, Mateusz
Szymański, Michał
Bruciak, Aleksandra
Gołębiowski, Tomasz
Musiał, Kinga
Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier
title Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier
title_full Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier
title_fullStr Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier
title_full_unstemmed Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier
title_short Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier
title_sort systemic immune inflammation index as a key predictor of dialysis in pediatric chronic kidney disease with the use of random forest classifier
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647735/
https://www.ncbi.nlm.nih.gov/pubmed/37959376
http://dx.doi.org/10.3390/jcm12216911
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