Basu Rajit K, Kaddourah Ahmad, Terrell Tara, Mottes Theresa, Arnold Patricia, Jacobs Judd, Andringa Jennifer, Armor Melissa, Hayden Lauren, Goldstein Stuart L
Center for Acute Care Nephrology, Cincinnati Children's Hospital and Medical Center, University of Cincinnati, USA.
Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital and Medical Center, University of Cincinnati, USA.
J Clin Trials. 2015;5(3). doi: 10.4172/2167-0870.1000222. Epub 2015 Apr 17.
Acute kidney injury (AKI) is associated with poor outcomes in critically ill children. Recent international consensus panels recommend standardized classification systems to improve the precision of AKI diagnosis, but there is a paucity of data to enable this refinement, particularly in pediatric critical care.
METHODS/DESIGN: This is a prospective observational study. We anticipate collecting data from more than 5500 critically ill children admitted to 32 pediatric intensive care units (PICUs) across the world, during the calendar year of 2014. Data will be collected continuously for three months at each center on all children older than 90 days and younger than 25 years admitted to the ICU. Demographic, resuscitative, and daily physiological and lab data will be captured at individual centers using MediData Rave™, a commercial system designed to manage and report clinical research data. Kidney specific measured variables include changes in serum creatinine and urine output, cumulative fluid overload (%), serum creatinine corrected for fluid balance, and KDIGO AKI stage. Urinary AKI biomarkers to be measured include: urinary neutrophil gelatinase lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid binding protein (l-FABP), and interleukin-18 (IL-18). Biomarker combinations will be created from different pairs and triplets of urinary biomarkers. The primary analysis will compare the discrimination of these panels versus changes in creatinine for prediction of severe AKI by Day 7 of ICU admission. Secondary analysis will investigate the prediction of biomarkers for injury 'time based phenotypes': duration (>2 days), severity (KDIGO stage, use of renal replacement therapy), reversibility (time to return of serum creatinine to baseline), association with fluid overload > 10%, and disease association (sepsis, hypovolemia, hypoxemia, or nephrotoxic).
The Assessment of Worldwide Acute Kidney Injury, Renal Angina and Epidemiology (AWARE) study will be the largest ever prospective study of any disease process in pediatric critical care. Data from AWARE will enable refinement of AKI classification. AWARE creates the largest ever all-cause pediatric AKI data warehouse and biologic sample repository, providing a broad and invaluable resource for critical care nephrologists seeking to study risk factors, prediction, identification, and treatment options for a disease syndrome with high associated morbidity affecting a significant proportion of hospitalized children. Improving the precision of AKI diagnosis using biomarker combinations provides a foundation for targeted, personalized therapy for different injury phenotypes.
NCT01987921.
急性肾损伤(AKI)与危重症儿童的不良预后相关。最近的国际共识小组推荐采用标准化分类系统来提高AKI诊断的准确性,但缺乏数据来实现这一改进,尤其是在儿科重症监护领域。
方法/设计:这是一项前瞻性观察性研究。我们预计在2014日历年期间,从全球32个儿科重症监护病房(PICU)收治的5500多名危重症儿童中收集数据。每个中心将对入住ICU的所有90天以上、25岁以下儿童连续三个月收集数据。人口统计学、复苏情况以及每日生理和实验室数据将在各个中心使用MediData Rave™收集,这是一个旨在管理和报告临床研究数据的商业系统。肾脏特异性测量变量包括血清肌酐和尿量的变化、累积液体超负荷(%)、经液体平衡校正的血清肌酐以及KDIGO AKI分期。待测量的尿AKI生物标志物包括:尿中性粒细胞明胶酶脂质运载蛋白(NGAL)、肾损伤分子-1(KIM-1)、肝型脂肪酸结合蛋白(l-FABP)和白细胞介素-18(IL-18)。生物标志物组合将由不同的尿生物标志物对和三联体组成。主要分析将比较这些组合与肌酐变化对入住ICU第7天严重AKI预测的辨别力。次要分析将研究生物标志物对损伤“基于时间的表型”的预测:持续时间(>2天)、严重程度(KDIGO分期、使用肾脏替代治疗)、可逆性(血清肌酐恢复至基线的时间)、与液体超负荷>10%的关联以及疾病关联(脓毒症、低血容量、低氧血症或肾毒性)。
全球急性肾损伤、肾绞痛及流行病学评估(AWARE)研究将是儿科重症监护领域有史以来对任何疾病过程进行的最大规模前瞻性研究。AWARE研究的数据将有助于完善AKI分类。AWARE创建了有史以来最大的全病因儿科AKI数据仓库和生物样本库,为重症监护肾病学家提供了一个广泛且宝贵的资源,这些专家旨在研究一种发病率高且影响相当比例住院儿童的疾病综合征的危险因素、预测、识别和治疗方案。使用生物标志物组合提高AKI诊断的准确性为针对不同损伤表型的靶向、个性化治疗奠定了基础。
NCT01987921。