Scholarlink

Objective <p>To investigate the association between endothelial activation and stress index (EASIX) and acute kidney injury (AKI) in heart failure (HF) patients.</p> Methods <p>The study utilized data from the MIMIC-IV database. EASIX was log-transformed to address its right-skewed distribution. The association of log EASIX with AKI and in-hospital mortality was assessed using logistic regression and Kaplan-Meier curves, and its discriminating performance was evaluated by the area under the receiver operating characteristic curve. A competing risk model was further employed, considering AKI occurrence as a primary event and in-hospital mortality as a competing event.</p> Results <p>Among 4,740 included HF patients, 53.143% were experiencing AKI. Log EASIX was an independent risk factor for AKI across three adjusted regression models (Model 1: OR = 3.398, 95%CI: 2.909–3.980; Model 2: OR = 5.788, 95%CI: 4.965–6.771; Model 3: OR = 2.331, 95%CI: 1.956–2.786), and demonstrated moderate discriminating performance (AUC = 0.704). Additionally, high log EASIX was associated with an increase in in-hospital mortality (<i>p</i> &lt; 0.05). Multivariable competing risk analyses exhibited an independent influence of log EASIX on AKI (<i>p</i> &lt; 0.05).</p> Conclusion <p>High log EASIX levels are associated with an increased risk of AKI in HF patients. In clinical practice, log EASIX, being simple to operate and readily accessible, may serve as an effective tool for the early identification of high-risk patients and help to develop individualized treatment strategies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Relationship of endothelial activation and stress index on concurrent acute kidney injury in patients with heart failure during intensive care unit: a competing risk model analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月5日

查看全文
  • Jun-wei Yu,
  • Chao-jian Yang,
  • Jie-feng Yang,
  • Jian-jiang Fang

摘要

Objective

To investigate the association between endothelial activation and stress index (EASIX) and acute kidney injury (AKI) in heart failure (HF) patients.

Methods

The study utilized data from the MIMIC-IV database. EASIX was log-transformed to address its right-skewed distribution. The association of log EASIX with AKI and in-hospital mortality was assessed using logistic regression and Kaplan-Meier curves, and its discriminating performance was evaluated by the area under the receiver operating characteristic curve. A competing risk model was further employed, considering AKI occurrence as a primary event and in-hospital mortality as a competing event.

Results

Among 4,740 included HF patients, 53.143% were experiencing AKI. Log EASIX was an independent risk factor for AKI across three adjusted regression models (Model 1: OR = 3.398, 95%CI: 2.909–3.980; Model 2: OR = 5.788, 95%CI: 4.965–6.771; Model 3: OR = 2.331, 95%CI: 1.956–2.786), and demonstrated moderate discriminating performance (AUC = 0.704). Additionally, high log EASIX was associated with an increase in in-hospital mortality (p < 0.05). Multivariable competing risk analyses exhibited an independent influence of log EASIX on AKI (p < 0.05).

Conclusion

High log EASIX levels are associated with an increased risk of AKI in HF patients. In clinical practice, log EASIX, being simple to operate and readily accessible, may serve as an effective tool for the early identification of high-risk patients and help to develop individualized treatment strategies.