Biomarkers Predict Progression of Acute Kidney Injury after Cardiac Surgery
Biomarkers Predict Progression of Acute Kidney Injury after Cardiac Surgery
复制标题
DOI：
10.1681/asn.2011090907
复制
发表时间：
2012-05-01
影响因子：
13.6
通讯作者：
Parikh, Chirag R.
中科院分区：
文献类型：
--
作者：
Koyner, Jay L.;Garg, Amit X.;Parikh, Chirag R.
能够预测AKI是否会进展可以改善监测和护理，指导患者咨询，并帮助登记参加AKI治疗试验。使用AKI研究中生物标记物终点的翻译研究(TRIBE-AKI)样本，我们评估了在心脏手术后早期AKI首次临床诊断时测量的肾脏损伤生物标记物是否可以预测AKI的严重程度。生物标记物包括尿IL-18、尿白蛋白/肌酐比(ACR)、尿和血浆中性粒细胞明胶酶相关脂蛋白(NGAL)；每项检测都是在至少发生AKI网络(AKI)1期的380名患者AKI诊断当天进行的。45名患者(11.8%)出现了主要终点(由恶化的相似分期定义的AKI进展)。使用多变量Logistic回归分析，我们确定AKI进展的风险。在调整了临床预测因素后，与最低的两个五分位数的生物标志物值相比，三个生物标志物中最高的五分位数仍然与AKI的进展有关：IL-18(优势比=3.0，95%可信区间=1.3-7.3)，ACR(优势比=3.4，95%可信区间=1.3-9.1)和血浆NGAL(优势比=7.7，95%可信区间=2.6-22.5)。与单独的临床模型相比，每个生物标志物都改善了风险分类，其中血浆NGAL的表现最好(无类别净重新分类改善0.69，P
Being able to predict whether AKI will progress could improve monitoring and care, guide patient counseling, and assist with enrollment into trials of AKI treatment. Using samples from the Translational Research Investigating Biomarker Endpoints in AKI study (TRIBE-AKI), we evaluated whether kidney injury biomarkers measured at the time of first clinical diagnosis of early AKI after cardiac surgery can forecast AKI severity. Biomarkers included urinary IL-18, urinary albumin to creatinine ratio (ACR), and urinary and plasma neutrophil gelatinase-associated lipocalin (NGAL); each measurement was on the day of AKI diagnosis in 380 patients who developed at least AKI Network (AKIN) stage 1 AKI. The primary end point (progression of AKI defined by worsening AKIN stage) occurred in 45 (11.8%) patients. Using multivariable logistic regression, we determined the risk of AKI progression. After adjustment for clinical predictors, compared with biomarker values in the lowest two quintiles, the highest quintiles of three biomarkers remained associated with AKI progression: IL-18 (odds ratio=3.0, 95% confidence interval=1.3-7.3), ACR (odds ratio=3.4, 95% confidence interval=1.3-9.1), and plasma NGAL (odds ratio=7.7, 95% confidence interval=2.6-22.5). Each biomarker improved risk classification compared with the clinical model alone, with plasma NGAL performing the best (category-free net reclassification improvement of 0.69, P