Menon Shina, Goldstein Stuart L, Mottes Theresa, Fei Lin, Kaddourah Ahmad, Terrell Tara, Arnold Patricia, Bennett Michael R, Basu Rajit K
Center for Acute Care Nephrology, Cincinnati Children's Hospital and Medical Center, University of Cincinnati, Cincinnati, OH, USA.
Department of Biostatistics, Cincinnati Children's Hospital and Medical Center, University of Cincinnati, Cincinnati, OH, USA Department of Pediatrics, Cincinnati Children's Hospital and Medical Center, University of Cincinnati, Cincinnati, OH, USA.
Nephrol Dial Transplant. 2016 Apr;31(4):586-94. doi: 10.1093/ndt/gfv457. Epub 2016 Feb 2.
The inconsistent ability of novel biomarkers to predict acute kidney injury (AKI) across heterogeneous patients and illnesses limits integration into routine practice. We previously retrospectively validated the ability of the renal angina index (RAI) to risk-stratify patients and provide context for confirmatory serum biomarker testing for the prediction of severe AKI.
We conducted this first prospective study of renal angina to determine whether the RAI on the day of admission (Day0) risk-stratified critically ill children for 'persistent, severe AKI' on Day 3 (Day3-AKI: KDIGO Stage 2-3) and whether incorporation of urinary biomarkers in the RAI model optimized AKI prediction.
A total of 184 consecutive patients (52.7% male) were included. Day0 renal angina was present (RAI ≥8) in 60 (32.6%) patients and was associated with longer duration of mechanical ventilation (P = 0.04), higher number of organ failure days (P = 0.003) and increased mortality (P < 0.001) than in patients with absence of renal angina. Day3-AKI was present in 15/156 (9.6%) patients; 12/15 (80%) fulfilled Day0 renal angina. Incorporation of urinary biomarkers into the RAI model increased the specificity and positive likelihood, and demonstrated net reclassification improvement (P < 0.001) for the prediction of Day3-AKI. Inclusion of urinary neutrophil gelatinase-associated lipocalin increased the area under the curve receiver-operating characteristic of RAI for Day3-AKI from 0.80 [95% confidence interval (CI): 0.58, 1.00] to 0.97 (95% CI: 0.93, 1.00).
We have now prospectively validated the RAI as a functional risk stratification methodology in a heterogeneous group of critically ill patients, providing context to direct measurement of novel urinary biomarkers and improving the prediction of severe persistent AKI.
新型生物标志物在不同患者和疾病中预测急性肾损伤（AKI）的能力不一致，这限制了其在常规临床实践中的应用。我们之前进行了回顾性研究，验证了肾绞痛指数（RAI）对患者进行风险分层的能力，并为预测严重AKI的血清生物标志物验证检测提供了背景信息。
我们开展了第一项关于肾绞痛的前瞻性研究，以确定入院当天（第0天）的RAI是否能对危重症儿童在第3天发生“持续性、严重AKI”（第3天-AKI：KDIGO 2-3期）进行风险分层，以及在RAI模型中纳入尿液生物标志物是否能优化AKI预测。
共纳入184例连续患者（52.7%为男性）。60例（32.6%）患者存在第0天肾绞痛（RAI≥8），与无肾绞痛的患者相比，这些患者机械通气时间更长（P = 0.04）、器官衰竭天数更多（P = 0.003）且死亡率更高（P < 0.001）。156例患者中有15例（9.6%）发生第3天-AKI；其中12/15（80%）符合第0天肾绞痛标准。在RAI模型中纳入尿液生物标志物可提高特异性和阳性似然比，并在预测第3天-AKI时显示出净重新分类改善（P < 0.001）。纳入尿中性粒细胞明胶酶相关脂质运载蛋白后使RAI预测第3天-AKI的受试者工作特征曲线下面积从0.80[95%置信区间（CI）：0.58，1.00]提高到0.97（95%CI：0.93，1.00）。
我们现已在前瞻性研究中验证了RAI作为一种功能风险分层方法在异质性危重症患者群体中的有效性，为直接检测新型尿液生物标志物提供了背景信息，并改善了对严重持续性AKI的预测。
