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      Early prediction of acute kidney injury biomarkers after endovascular stent graft repair of aortic aneurysm: a prospective observational study

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          Abstract

          Background

          Acute kidney injury (AKI) is a common and serious condition usually detected some time after onset by changes in serum creatinine (sCr). Although stent grafting to repair aortic aneurysms is associated with AKI caused by surgical procedures or the use of contrast agents, early biomarkers for AKI have not been adequately examined in stent graft recipients. We studied biomarkers including urinary neutrophil gelatinase-associated lipocalin (NGAL), blood NGAL, N-acetyl-β- d-glucosaminidase (NAG), microalbumin (Alb), and liver fatty acid-binding protein (L-FABP) as prospective early biomarkers for AKI in patients who had received stent graft repairs of aortic aneurysms.

          Methods

          In addition to pre-surgical sampling, at 2 to 6 h and at 1, 3 to 4, and 5 days or later (until stable) after surgery, urine and serum biomarkers were sampled from 47 patients who underwent stent graft repair of aortic aneurysms.

          Results

          Using Acute Kidney Injury Network criteria, 6 (14%) of 42 retained patients developed AKI. NGAL corrected with urine Cr (NGAL/Cr) values demonstrated the best predictive value for AKI (97% specificity, 83% sensitivity at a 65.1 μg/gCr cutoff). The area under the receiver-operator characteristic curve of NGAL/Cr value 2 h after surgery was 0.9. Although NGAL/Cr, L-FABP corrected with urine Cr (L-FABP/Cr), L-FABP, NAG, and Alb corrected by urine Cr (Alb/Cr) all reached peak values before AKI detection by sCr in AKI patients, all biomarkers reached the cutoff value before AKI detection after adaption of cutoff value.

          Conclusions

          After stent graft repair of aortic aneurysm, NGAL/Cr is a potentially useful early biomarker for AKI.

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          Most cited references13

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          Biomarkers predict progression of acute kidney injury after cardiac surgery.

          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<0.0001). In conclusion, biomarkers measured on the day of AKI diagnosis improve risk stratification and identify patients at higher risk for progression of AKI and worse patient outcomes.
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            Refining predictive models in critically ill patients with acute renal failure.

            Mortality rates in acute renal failure remain extremely high, and risk-adjustment tools are needed for quality improvement initiatives and design (stratification) and analysis of clinical trials. A total of 605 patients with acute renal failure in the intensive care unit during 1989-1995 were evaluated, and demographic, historical, laboratory, and physiologic variables were linked with in-hospital death rates using multivariable logistic regression. Three hundred and fourteen (51.9%) patients died in-hospital. The following variables were significantly associated with in-hospital death: age (odds ratio [OR], 1.02 per yr), male gender (OR, 2.36), respiratory (OR, 2.62), liver (OR, 3.06), and hematologic failure (OR, 3.40), creatinine (OR, 0.71 per mg/dl), blood urea nitrogen (OR, 1.02 per mg/dl), log urine output (OR, 0.64 per log ml/d), and heart rate (OR, 1.01 per beat/min). The area under the receiver operating characteristic curve was 0.83, indicating good model discrimination. The model was superior in all performance metrics to six generic and four acute renal failure-specific predictive models. A disease-specific severity of illness equation was developed using routinely available and specific clinical variables. Cross-validation of the model and additional bedside experience will be needed before it can be effectively applied across centers, particularly in the context of clinical trials.
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              Early Diagnosis of Acute Kidney Injury: The Promise of Novel Biomarkers

              The incidence of acute kidney injury (AKI) formerly referred to as acute renal failure (ARF) is increasing to epidemic proportions. Development of AKI portends excessive morbidity and mortality. AKI is associated with prolonged hospital stay, increased healthcare costs and high mortality especially in critically ill patients. The mortality rate has remained largely unchanged for many decades. Delay in the diagnosis of AKI using conventional biomarkers like urine output and serum creatinine has been one of the important obstacles in applying effective early interventions. Several new biomarkers are being evaluated in a quest for early diagnosis of AKI, among which neutrophil gelatinase-associated lipocalin (NGAL) appears to be one of the most promising. This review summarizes the recent literature on these biomarkers.
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                Author and article information

                Contributors
                Journal
                J Intensive Care
                J Intensive Care
                Journal of Intensive Care
                BioMed Central
                2052-0492
                2014
                31 July 2014
                : 2
                : 45
                Affiliations
                [1 ]Department of Anesthesiology and Intensive Care, Graduate School of Medicine, Osaka University, 2-15, Yamadaoka, Suita 565-0871, Japan
                [2 ]Department of Cardiovascular Surgery, Graduate School of Medicine, Chiba University, 1-8-1, Inohana, Chuo-ku 260-8670, Chiba, Japan
                [3 ]Department of Cardiovascular Surgery, Graduate School of Medicine, Osaka University, 2-15, Yamadaoka, Suita 565-0871, Japan
                Article
                s40560-014-0045-4
                10.1186/s40560-014-0045-4
                4424764
                25960881
                e0ac5130-e0f4-4372-9ddc-64f4c226bad1
                Copyright © 2014 Ueta et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 April 2014
                : 23 June 2014
                Categories
                Research

                acute kidney injury,neutrophil gelatinase-associated lipocalin,biomarkers,endovascular aortic repair

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