将生物标志物与肾绞痛指数相结合用于预测危重症儿童的严重急性肾损伤。
Incorporation of biomarkers with the renal angina index for prediction of severe AKI in critically ill children.
作者信息
Basu Rajit K, Wang Yu, Wong Hector R, Chawla Lakhmir S, Wheeler Derek S, Goldstein Stuart L
机构信息
Center for Acute Care Nephrology,, Divisions of ‡Critical Care and, §Biostatistics and Epidemiology, and, ¶The Heart Institute, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio;, †Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, ‖Division of Anesthesiology and Critical Care Medicine, George Washington University, Washington, DC.
出版信息
Clin J Am Soc Nephrol. 2014 Apr;9(4):654-62. doi: 10.2215/CJN.09720913. Epub 2014 Mar 27.
BACKGROUND AND OBJECTIVES
Novel AKI biomarkers carry variable performance for prediction of AKI in patients with heterogeneous illness. Until utility is demonstrated in critically ill patients outside of the cardiopulmonary bypass population, AKI biomarkers are unlikely to gain widespread implementation. Operationalization of an AKI risk stratification methodology, termed renal angina, was recently reported to enhance prediction at the time of intensive care unit admission for persistent severe AKI. The renal angina index (RAI) was developed to provide the clinical context to direct AKI biomarker testing. This study tested the hypothesis that incorporation of AKI biomarkers in patients fulfilling renal angina improves the prediction of persistent severe AKI.
DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In a multicenter study of 214 patients admitted to the pediatric intensive care unit with sepsis, the discrimination of plasma neutrophil gelatinase-associated lipocalin (NGAL), matrix metalloproteinase-8 (MMP-8), and neutrophil elastase-2 (Ela-2) were determined individually and in combination with the RAI for severe AKI. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated.
RESULTS
Individual biomarkers demonstrated marginal discrimination for severe AKI (area under curve [AUC]: NGAL, 0.72; MMP-8, 0.68; Ela-2, 0.72), inferior to prediction by the clinical model of the RAI (AUC=0.80). Incorporation of each biomarker significantly added to the renal angina model AKI prediction (AUC=0.80, increased to 0.84-0.88; P<0.05 for each). The inclusion of each biomarker with the RAI demonstrated NRI (0.512, 0.428, and 0.545 for NGAL, MMP-8, and Ela-2, respectively; all P<0.03) and IDI (0.075 for Ela-2). The inclusion of both Ela-2 and NGAL with RAI demonstrated an NRI of 0.871 (P<0.001) and an IDI of 0.1 (P=0.01).
CONCLUSIONS
This study shows that incorporation of AKI biomarkers into the RAI improves discrimination for severe AKI. The RAI optimizes the utility of AKI biomarkers in a heterogeneous, critically ill patient population.
背景与目的
新型急性肾损伤（AKI）生物标志物在预测患有多种疾病的患者发生AKI时表现各异。在体外循环人群以外的重症患者中，若未证明其效用，AKI生物标志物不太可能得到广泛应用。最近有报道称，一种名为肾绞痛的AKI风险分层方法的实施可提高重症监护病房收治持续性严重AKI患者时的预测能力。肾绞痛指数（RAI）的制定是为了提供指导AKI生物标志物检测的临床背景。本研究检验了这样一个假设，即在符合肾绞痛标准的患者中纳入AKI生物标志物可改善对持续性严重AKI的预测。
设计、地点、参与者与测量：在一项对214名因脓毒症入住儿科重症监护病房的患者进行的多中心研究中，分别测定了血浆中性粒细胞明胶酶相关脂质运载蛋白（NGAL）、基质金属蛋白酶-8（MMP-8）和中性粒细胞弹性蛋白酶-2（Ela-2）对严重AKI的鉴别能力，并将其与RAI结合用于严重AKI的预测。计算了净重新分类改善（NRI）和综合鉴别改善（IDI）。
结果
单个生物标志物对严重AKI的鉴别能力有限（曲线下面积[AUC]：NGAL为0.72；MMP-8为0.68；Ela-2为0.72），不如RAI临床模型的预测能力（AUC = 0.80）。将每个生物标志物纳入肾绞痛模型可显著提高AKI预测能力（AUC = 0.80，提高至0.84 - 0.88；每个P < 0.05）。将每个生物标志物与RAI结合显示出NRI（NGAL、MMP-8和Ela-2分别为0.512、0.428和0.545；均P < 0.03）和IDI（Ela-2为0.075）。将Ela-2和NGAL都与RAI结合显示出NRI为0.871（P <
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