PDF(Pubmed)
Abstract：
Children undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are prone to developing acute kidney injury (AKI). Markers of kidney damage: kidney injury molecule (KIM)-1, interleukin (IL)-18, and neutrophil gelatinase-associated lipocalin (NGAL) may ease early diagnosis of AKI. The aim of this study was to assess serum concentrations of KIM-1, IL-18, and NGAL in children undergoing HSCT in relation to classical markers of kidney function (creatinine, cystatin C, estimated glomerular filtration rate (eGFR)) and to analyze their usefulness as predictors of kidney damage with the use of artificial intelligence tools. Serum concentrations of KIM-1, IL-18, NGAL, and cystatin C were assessed by ELISA in 27 children undergoing HSCT before transplantation and up to 4 weeks after the procedure. The data was used to build a Random Forest Classifier (RFC) model of renal injury prediction. The RFC model established on the basis of 3 input variables, KIM-1, IL-18, and NGAL concentrations in the serum of children before HSCT, was able to effectively assess the rate of patients with hyperfiltration, a surrogate marker of kidney injury 4 weeks after the procedure. With the use of the RFC model, serum KIM-1, IL-18, and NGAL may serve as markers of incipient renal dysfunction in children after HSCT.
摘要：
接受异基因造血干细胞移植（HSCT）的儿童容易发生急性肾损伤（AKI）。肾损伤标志物：肾损伤分子（KIM）-1，白细胞介素（IL）-18和中性粒细胞明胶酶相关脂质运载蛋白（NGAL）可能有助于AKI的早期诊断。这项研究的目的是评估接受HSCT的儿童中KIM-1，IL-18和NGAL的血清浓度与肾功能的经典标志物（肌酐，胱抑素C,估计的肾小球滤过率（eGFR）），并使用人工智能工具分析其作为肾脏损害预测因子的有用性。血清KIM-1，IL-18，NGAL，对27例接受HSCT的儿童在移植前和手术后4周进行ELISA和胱抑素C评估。数据用于构建肾损伤预测的随机森林分类器(RFC)模型。基于3个输入变量建立的RFC模型,HSCT前儿童血清中KIM-1、IL-18和NGAL的浓度,能够有效地评估患者的过度滤过率，手术后4周肾脏损伤的替代标记。随着RFC模型的使用，血清KIM-1、IL-18和NGAL可作为儿童HSCT术后早期肾功能不全的标志物。
