Neutrophil Gelatinase-Associated Lipocalin Cutoff Value Selection and Acute Kidney Injury Classification System Determine Phenotype Allocation and Associated Outcomes

中性粒细胞明胶酶相关脂质运载蛋白临界值选择和急性肾损伤分类系统决定表型分配及相关结局

阅读:1

Abstract

BACKGROUND: We explored the extent to which neutrophil gelatinase-associated lipocalin (NGAL) cutoff value selection and the acute kidney injury (AKI) classification system determine clinical AKI-phenotype allocation and associated outcomes. METHODS: Cutoff values from ROC curves of data from two independent prospective cardiac surgery study cohorts (Magdeburg and Berlin, Germany) were used to predict Kidney Disease: Improving Global Outcome (KDIGO)- or Risk, Injury, Failure, Loss of kidney function, End-stage (RIFLE)-defined AKI. Statistical methodologies (maximum Youden index, lowest distance to [0, 1] in ROC space, sensitivity≍specificity) and cutoff values from two NGAL meta-analyses were evaluated. Associated risks of adverse outcomes (acute dialysis initiation and in-hospital mortality) were compared. RESULTS: NGAL cutoff concentrations calculated from ROC curves to predict AKI varied according to the statistical methodology and AKI classification system (10.6-159.1 and 16.85-149.3 ng/mL in the Magdeburg and Berlin cohorts, respectively). Proportions of attributed subclinical AKI ranged 2%-33.0% and 10.1%-33.1% in the Magdeburg and Berlin cohorts, respectively. The difference in calculated risk for adverse outcomes (fraction of odds ratios for AKI-phenotype group differences) varied considerably when changing the cutoff concentration within the RIFLE or KDIGO classification (up to 18.33- and 16.11-times risk difference, respectively) and was even greater when comparing cutoff methodologies between RIFLE and KDIGO classifications (up to 25.7-times risk difference). CONCLUSIONS: NGAL positivity adds prognostic information regardless of RIFLE or KDIGO classification or cutoff selection methodology. The risk of adverse events depends on the methodology of cutoff selection and AKI classification system.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。