Identifying acute kidney injury subtypes based on serum electrolyte data in ICU via K-medoids clustering.

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01
Wentie Liu, Tongyue Shi, Haowei Xu, Huiying Zhao, Jianguo Hao, Guilan Kong
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Abstract

This study proposes to use the K-medoids clustering method to identify subtypes of Intensive Care Unit (ICU)-acquired acute kidney injury (AKI) patients based on serum electrolyte data. Three distinct AKI subtypes with different serum electrolyte characteristics were identified by clustering analysis. Further, descriptive analysis was employed to characterize in-hospital mortality and renal replacement therapy, diuretic and vasopressor usage in the three subtypes, and Chi-square tests were conducted to check the differences of prognosis and treatments among the identified subtypes. This study enables the subclassification of AKI patients in the ICU, facilitating ICU physicians to make timely clinical decisions about AKI, and ultimately may contribute to patient outcome improvement.

基于ICU患者血清电解质数据的K-medoids聚类识别急性肾损伤亚型。
本研究提出基于血清电解质数据,采用K-medoids聚类方法识别重症监护病房(ICU)获得性急性肾损伤(AKI)患者的亚型。聚类分析发现3种不同的AKI亚型具有不同的血清电解质特征。进一步,采用描述性分析对三种亚型患者的住院死亡率和肾脏替代治疗、利尿剂和血管加压剂的使用情况进行表征,并采用卡方检验检验所确定亚型患者的预后和治疗差异。本研究实现了AKI患者在ICU的亚分类,有助于ICU医生对AKI做出及时的临床决策,最终可能有助于患者预后的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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