Liu Hsin-Hung, Wang Yu-Tseng, Yang Meng-Han, Lin Wei-Shu Kevin, Oyang Yen-Jen
Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei City 10617, Taiwan.
Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei City 10617, Taiwan.
Diagnostics (Basel). 2023 Jul 31;13(15):2551. doi: 10.3390/diagnostics13152551.
Assessing the risk of acute kidney injury (AKI) has been a challenging issue for clinicians in intensive care units (ICUs). In recent years, a number of studies have been conducted to investigate the associations between several serum electrolytes and AKI. Nevertheless, the compound effects of serum creatinine, blood urea nitrogen (BUN), and clinically relevant serum electrolytes have yet to be comprehensively investigated. Accordingly, we initiated this study aiming to develop machine learning models that illustrate how these factors interact with each other. In particular, we focused on ICU patients without a prior history of AKI or AKI-related comorbidities. With this practice, we were able to examine the associations between the levels of serum electrolytes and renal function in a more controlled manner. Our analyses revealed that the levels of serum creatinine, chloride, and magnesium were the three major factors to be monitored for this group of patients. In summary, our results can provide valuable insights for developing early intervention and effective management strategies as well as crucial clues for future investigations of the pathophysiological mechanisms that are involved. In future studies, subgroup analyses based on different causes of AKI should be conducted to further enhance our understanding of AKI.
评估急性肾损伤（AKI）风险一直是重症监护病房（ICU）临床医生面临的一个具有挑战性的问题。近年来，已经开展了多项研究来调查几种血清电解质与AKI之间的关联。然而，血清肌酐、血尿素氮（BUN）和临床相关血清电解质的复合效应尚未得到全面研究。因此，我们启动了这项研究，旨在开发机器学习模型，以阐明这些因素是如何相互作用的。特别是，我们关注的是没有AKI既往史或AKI相关合并症的ICU患者。通过这种做法，我们能够以更可控的方式研究血清电解质水平与肾功能之间的关联。我们的分析表明，血清肌酐、氯和镁的水平是该组患者需要监测的三个主要因素。总之，我们的结果可为制定早期干预和有效管理策略提供有价值的见解，并为未来涉及的病理生理机制研究提供关键线索。在未来的研究中，应基于AKI的不同病因进行亚组分析，以进一步加深我们对AKI的理解。
