Urinary angiotensinogen predicts adverse outcomes among acute kidney injury patients in the intensive care unit
© Alge et al.; licensee BioMed Central Ltd. 2013
Received: 16 November 2012
Accepted: 5 April 2013
Published: 15 April 2013
Acute kidney injury (AKI) is commonly observed in the intensive care unit (ICU), where it can be caused by a variety of factors. The objective of this study was to evaluate the prognostic value of urinary angiotensinogen, a candidate prognostic AKI biomarker identified in post-cardiac surgery patients, in this heterogeneous population.
Urinary angiotensinogen was measured by ELISA and corrected for urine creatinine in 45 patients who developed AKI in the ICU. Patients were grouped by AKI etiology, and the angiotensinogen-to-creatinine ratio (uAnCR) was compared among the groups using the Kruskal-Wallis test. The ability of uAnCR to predict the following endpoints was tested using the area under the ROC curve (AUC): the need for renal replacement therapy (RRT) or death, increased length of stay (defined as hospital discharge > 7 days or death ≤ 7 days from sample collection), and worsening AKI (defined as an increase in serum creatinine > 0.3 mg/dL after sample collection or RRT).
uAnCR was significantly elevated in patients who met the composite outcome RRT or death (89.4 vs 25.4 ng/mg; P = 0.01), and it was a strong predictor of this outcome (AUC = 0.73). Patients with uAnCR values above the median for the cohort (55.21 ng/mg) had increased length of stay compared to patients with uAnCR ≤ 55.21 ng/mg (22 days vs 7 days after sample collection; P = 0.01). uAnCR was predictive of the outcome increased length of stay (AUC = 0.77). uAnCR was also a strong predictor of worsening of AKI (AUC = 0.77). The uAnCR of patients with pre-renal AKI was lower compared to patients with AKI of other causes (median uAnCR 11.3 vs 80.2 ng/mg; P = 0.02).
Elevated urinary angiotensinogen is associated with adverse events in AKI patients in the ICU. It could be used to identify high risk patients who would benefit from timely intervention that could improve their outcomes.
Acute kidney injury (AKI) is reflected by an increase in serum creatinine (sCr) or a decrease in urine output, the magnitude of which is used to assess the severity of renal injury using the risk, injury, failure, loss, end-stage renal failure (RIFLE) or Acute Kidney Injury Network (AKIN) staging systems [1, 2]. A patient's risk of both short- and long-term adverse outcomes is correlated with the severity of AKI as determined using these staging systems [3–7]. For example, a large retrospective cohort study of a critically ill population reported that the odds ratio (OR) for in-hospital mortality increased from 2.07 in AKIN stage 1 patients to 2.99 in AKIN stage 3 patients . However, because sCr does not reach steady state until after an acute reduction in glomerular filtration rate (GFR) has occurred, the severity of AKI can only be definitively determined late in the disease. The conceptual framework for understanding AKI proposed by Murray et al. underscores the importance of progression from the early stages of AKI, in which an at-risk patient experiences renal injury, to later stages of the disease, which include decreased GFR, renal failure, and death . Similarly, the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline for AKI highlights the need for accurate assessment of a patient's risk of adverse outcomes, notably progression to a more severe stage of AKI after renal injury has occurred .
Unfortunately, it is difficult to determine if a patient with a small increase in sCr will worsen, improve, or stay the same. Furthermore, it is not possible to differentiate mild from severe AKI at an early time point using conventional diagnostic criteria. Biomarkers that reflect the magnitude of tubular injury at the time they are collected could serve this function. Novel AKI biomarkers such as kidney injury molecule 1 (KIM-1), neutrophil gelatinase associated lipocalin (NGAL), IL-18, and Cystatin C can diagnose AKI prior to detectable changes in sCr [11–19]. However, two recent studies have reported unadjusted area under the curve (AUC) values for prediction of worsening AKI between 0.58 and 0.71, suggesting that diagnostic AKI biomarkers are of lesser predictive value among patients who already have established AKI [20, 21]. Therefore, prognostic biomarkers that predict outcomes in patients with established AKI are needed.
We recently identified urinary angiotensinogen as a novel prognostic biomarker, capable of predicting adverse outcomes including worsening of AKI and the need for renal replacement therapy after cardiac surgery . However, AKI is a heterogenous syndrome that can be caused by many precipitating factors other than surgery, and it is common among critically ill patients. Because the prognostic predictive power of an AKI biomarker may differ with the pathobiology underlying the etiology it is necessary to determine if the prognostic predictive value of angiotensinogen is generalizable to AKI of other etiologies. Therefore, in the current study we investigated the prognostic predictive power of angiotensinogen in a cohort of critically ill, non-surgical patients in the ICU, who developed AKI.
Materials and methods
Patients and urine samples
All patients (n = 45) had been admitted to the ICU at the Medical University of South Carolina (MUSC) Hospital. Patients either had AKI at ICU admission or developed AKI during their stay in the ICU. AKI was defined according to the AKIN criteria . When possible, baseline sCr was defined as the most recent (within 1 month) value prior to the AKI episode. When antecedent sCr values were not available, the lowest sCr observed during the patient's hospital stay was used as the baseline. Informed consent was obtained from the patients or their next of kin prior to urine sample collection, in accordance with the MUSC Institutional Review Board approved protocols. The only exclusion criteria were initiation of renal replacement therapy (RRT) prior to sample collection and non-consent. Patients for this study were selected retrospectively to perform a case-control study of ICU patients diagnosed with AKI at the time of urine sample collection. The primary outcome was the need for renal replacement therapy or death, and patients who had AKI at the time of sample collection but did not meet the primary outcome were selected as controls. Decisions about initiating RRT were made by the clinical attending physician. Samples were collected at the time that the diagnosis of AKI was made. If patients had AKI on admission, samples were collected immediately after admission. Urine samples were processed according to a standard operating procedure. They were treated with a protease inhibitor cocktail (Roche, Indianopolis, IN), Mini, ethylenediaminetetraacetic acid (EDTA)-free), centrifuged for 10 minutes at 1,000 × g and the supernatant was aspirated and stored at -80°C until the time of use. Clinical data were obtained by retrospective chart review. Etiology of AKI was determined and patients were assigned to one of four categories: pre-renal, ischemic Acute tubular necrosis (ATN), sepsis-associated AKI, and other. Pre-renal AKI was defined as an episode of AKI in the setting of hypotension or hypovolemia in which the patient's sCr decreased to < 150% of baseline within 48 hours after diagnosis. Ischemic ATN was defined as severe, prolonged AKI following any event that compromises renal blood flow or oxygen delivery. The specific events observed in our cohort included ruptured abdominal aortic aneurysm, cardiogenic shock, and exacerbation of congestive heart failure. Patients for whom the etiology could not be determined or was multifactorial were included in the category, other.
Determination of urinary angiotensinogen-to-creatinine ratio
Urinary angiotensinogen was measured using the Human Total Angiotensinogen Assay Kit (Immuno-Biological Laboratories Co., Ltd., IBL-America, Minneapolis, MN, USA), a solid-phase sandwich ELISA, according to the manufacturer's protocol. Urine creatinine was measured using the Jaffe assay and used to correct the urine angiotensinogen concentration as was done in the previous analysis of angiotensinogen as a biomarker after cardiac surgery. Values were reported as the ratio of angiotensinogen in ng/ml to creatinine in mg/ml (uAnCR, ng/mg). The AUC value was higher for the primary outcome when creatinine corrected values were used (not shown).
The primary outcome was the composite outcome of the need for RRT or death. Increased length of hospital stay was defined as hospital discharge > 7 days from the day of sample collection or death ≤ 7 days from sample collection. Worsening of AKI was defined as an additional increase in sCr > 0.3 mg/dL from the sCr at the time of the urine sample collection or the initiation of RRT.
The Kruskal-Wallis test and post hoc Dunn's test were used to compare the uAnCR values of patients grouped by AKI etiology. The Mann-Whitney U-test was used when only two groups were compared. Other continuous variables were compared using the t- test or Mann-Whitney U-test. Categorical variables were compared using the chi squared (χ2) or Fisher's exact tests. Logistic regression was used to determine the multiplicative OR for a one SD increase in uAnCR. However, because uAnCR was not normally distributed, it was first log10 transformed for this analysis. Receiver operator characteristic (ROC) curves were used to test the ability of uAnCR to predict outcomes, and the AUC was used as an estimate of an overall accuracy of the biomarker. The ROC curve was considered statistically significant if the AUC differed from 0.5, as determined by the z-test. Optimal cutoffs were determined by selecting the data point that minimized the geometric distance from 100% sensitivity and 100% specificity on the ROC curve. Additional cutoffs were determined by selecting the points on the ROC at which the positive and negative likelihood ratios were maximized and minimized, respectively. The Spearman's correlation coefficient was used to determine the correlation between uAnCR and length of hospital stay. Kaplan-Meier curves were used to visualize the relationship between uAnCR and length of hospital stay. Patients who died were censored. The log rank test was used to compare the curves. Cox regression was used to calculate the proportional hazard ratio for time to discharge comparing patients with high and low uAnCR (defined as > the median or ≤ the median of the cohort). The Cox proportional hazard model included both the patient's uAnCR and AKIN stage at collection.
Characteristics of ICU patients used to verify the prognostic predictive power of urinary angiotensinogen as an acute kidney injury biomarker
No RRT and Survival
RRT or Death
Number of patients
62.9 ± 16.1
54.4 ± 17.6
Caucasian, % (n)
Male, % (n)
AKI etiology, n (%)
Serum creatinine (sCr), mg/dL
1.15 (0.8, 1.6)
1.1 (1.0, 1.5)
sCr at collectiona
2.1 ± 0.8
2.5 ± 0.8
Change in sCrb, %
150 (130 to 189)
200 (150 to 257)
AKIN stage at collection
Outcomes, % patients (n)
MAP on day of collectionb
74.9 (70.4 to 86.8)
68.6 (64.5 to 84.1)
History of HTN, % patients (n)
History of diabetes mellitus, % patients (n)
History of ACE inhibitor or ARB use, % patients (n)
Angiotensinogen predicts RRT or death
Length of hospital stay
Worsening of AKI
Urinary angiotensinogen by AKI etiology
Summary of performance characteristics of urinary angiotensinogen as a predictor of outcomes among acute kidney injury patients
RRT or deathb
(0.58 to 0.88)
Best: > 34.76
Max LR+: > 230.0
Min LR-: ≤ 7.58
(0.63 to 0.92)
Best: > 59.61
Max LR+: > 123.5
Min LR-: ≤ 3.31
(0.63 to 0.91)
Best: > 34.76
Max LR+: > 230.0
Min LR-: ≤ 21.24
In this study we also used the maximum LR+ and minimum LR- to define cutoffs at which patients could be stratified into high risk and low risk groups for each outcome, and showed that using these cutoffs, the risk of a significant percentage of the cohort could be assigned with a high level of confidence. We evaluated multiple cutoff values since the purpose of a biomarker affects the threshold that will be used. This approach could be particularly useful for screening patients for enrollment into a clinical trial to enrich the study population with patients who will meet the outcome. For instance, a study to test the efficacy of early initiation of RRT could use as an inclusion criterion a uAnCR value > 230 ng/mg. Using this cutoff we identified 43.5% of the patients who would require RRT or die, while excluding 95.5% of patients who would not meet the endpoint. Therefore, if a target enrollment of 500 is assumed, we would only enroll 45 patients who would not meet the endpoint RRT or death, and who would gain no survival benefit from the intervention. However, using this cutoff we need to screen a total of 2,083 patients to meet the target enrollment. Of the 1,583 patients screened but not enrolled, 589 would eventually meet the endpoint, and so the benefit of enrichment would need to be weighed against the cost of screening.
Our findings could also have important implications for our understanding of the pathobiology of AKI. Angiotensinogen is the principal substrate of renin, and a major driver of activation of the renin-angiotensin system (RAS). Animal studies have suggested a role for the RAS in the molecular mechanisms of AKI. It has been observed that angiotensin II increases and angiotensin 1-7, the molecular counterbalance of angiotensin II decreases in kidney tissue following ischemia reperfusion injury in rats [28, 29]. Angiotensin II can contribute to renal injury through pro-inflammatory effects mediated by the nuclear factor-κB (NF-κB) pathway, and it has been demonstrated that inhibition of angiotensin converting enzyme and the angiotensin II type 1 receptor with captopril and losartan, respectively, reduce renal inflammation and mitigate the severity of AKI in rats subjected to renal ischemia reperfusion injury [30, 31]. Interestingly, intrarenal angiotensin II concentration strongly correlates with urinary angiotensinogen concentration (r = 0.79), but is not correlated with plasma angiotensinogen . Our findings are suggestive of a role of the RAS in modulating the severity of AKI, a notion which is supported by a recent study in which an association was reported between severity of tubular atrophy and urinary angiotensinogen among individuals with chronic kidney disease .
Urinary AnCR could be useful as a prognostic AKI biomarker in the setting of the ICU. It could be used to evaluate a patient's risk of adverse outcomes, potentially leading to an altered interventional strategy or improved enrollment in clinical trials. Angiotensinogen also appears to discriminate between AKI of pre-renal etiology and other etiologies and may be useful to discriminate between patients with pre-renal azotemia and intrinsic renal injury.
Urinary angiotensinogen could be used as a prognostic biomarker of AKI in the ICU.
Urinary angiotensinogen predicts adverse outcomes in patients with AKI and could be used in clinical trial design to enrich the study population with patients who might benefit from intervention.
Urinary angiotensinogen has the potential to be useful in the discrimination of pre-renal AKI from intrinsic AKI.
Urinary angiotensinogen concentrations could reflect activation of the intrarenal RAS during AKI.
acute kidney injury
Acute Kidney Injury Network
area under the curve of a receiver operator characteristics curve
enzyme-linked immunosorbent assay
fractional excretion of sodium
fractional excretion of urea
glomerular filtration rate
Kidney Disease: Improving Global Outcomes
kidney injury molecule 1
length of stay
positive likelihood ratio
negative likelihood ratio
Medical University of South Carolina
nuclear factor -kB
neutrophil gelatinase associated lipocalin
renin angiotensin system
risk, injury, failure, loss, end-stage renal failure
receiver operator characteristics
renal replacement therapy
urinary angiotensinogen to creatinine ratio.
This study was supported by NIH grant numbers R01 DK080234 and UL1 RR029882 and by a Merit Review award from the Biomedical Laboratory Research and Development Program of the Department of Veterans Affairs. The contents do not necessarily represent the views of the Department of Veterans Affairs or the United States Government.
Additional members of the SAKInet consortium (http://www.sakinet.org): Medical University of South Carolina - Elizabeth G Hill, Milos N Budisavljevic, Rick G Schnellmann; Duke University - Andrew D Shaw; George Washington University - Lakhmir S Chawla; University of Tennessee College of Medicine (Chattanooga) - James A Tumlin; Vanderbilt University - Frederick T (Josh) Billings, T Alp Ikizler, Eddie D Siew.
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