Dataset Information

Urinary angiotensinogen predicts adverse outcomes among acute kidney injury patients in the intensive care unit.

ABSTRACT:

Introduction

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.

Methods

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).

Results

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).

Conclusions

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.

SUBMITTER: Alge JL

PROVIDER: S-EPMC3672721 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Urinary angiotensinogen predicts adverse outcomes among acute kidney injury patients in the intensive care unit.

Alge Joseph L JL Karakala Nithin N Neely Benjamin A BA Janech Michael G MG Velez Juan Carlos Q JC Arthur John M JM

Critical care (London, England) 20130415 2

<h4>Introduction</h4>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.<h4>Methods</h4>Urinary angiotensinogen was measured by ELISA and corrected for urine creatinine in 45 patients who developed AKI in the ICU. ...[more]

PMID: 23587112

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Project description:BackgroundAcute kidney injury (AKI) represents a significant global health challenge, leading to increased patient distress and financial health care burdens. The development of AKI in intensive care unit (ICU) settings is linked to prolonged ICU stays, a heightened risk of long-term renal dysfunction, and elevated short- and long-term mortality rates. The current diagnostic approach for AKI is based on late indicators, such as elevated serum creatinine and decreased urine output, which can only detect AKI after renal injury has transpired. There are no treatments to reverse or restore renal function once AKI has developed, other than supportive care. Early prediction of AKI enables proactive management and may improve patient outcomes.ObjectiveThe primary aim was to develop a machine learning algorithm, NAVOY Acute Kidney Injury, capable of predicting the onset of AKI in ICU patients using data routinely collected in ICU electronic health records. The ultimate goal was to create a clinical decision support tool that empowers ICU clinicians to proactively manage AKI and, consequently, enhance patient outcomes.MethodsWe developed the NAVOY Acute Kidney Injury algorithm using a hybrid ensemble model, which combines the strengths of both a Random Forest (Leo Breiman and Adele Cutler) and an XGBoost model (Tianqi Chen). To ensure the accuracy of predictions, the algorithm used 22 clinical variables for hourly predictions of AKI as defined by the Kidney Disease: Improving Global Outcomes guidelines. Data for algorithm development were sourced from the Massachusetts Institute of Technology Lab for Computational Physiology Medical Information Mart for Intensive Care IV clinical database, focusing on ICU patients aged 18 years or older.ResultsThe developed algorithm, NAVOY Acute Kidney Injury, uses 4 hours of input and can, with high accuracy, predict patients with a high risk of developing AKI 12 hours before onset. The prediction performance compares well with previously published prediction algorithms designed to predict AKI onset in accordance with Kidney Disease: Improving Global Outcomes diagnosis criteria, with an impressive area under the receiver operating characteristics curve (AUROC) of 0.91 and an area under the precision-recall curve (AUPRC) of 0.75. The algorithm's predictive performance was externally validated on an independent hold-out test data set, confirming its ability to predict AKI with exceptional accuracy.ConclusionsNAVOY Acute Kidney Injury is an important development in the field of critical care medicine. It offers the ability to predict the onset of AKI with high accuracy using only 4 hours of data routinely collected in ICU electronic health records. This early detection capability has the potential to strengthen patient monitoring and management, ultimately leading to improved patient outcomes. Furthermore, NAVOY Acute Kidney Injury has been granted Conformite Europeenne (CE)-marking, marking a significant milestone as the first CE-marked AKI prediction algorithm for commercial use in European ICUs.

Project description:BackgroundsPredicting the development of acute kidney injury (AKI) in the critical care setting is challenging. Although several biomarkers showed somewhat satisfactory performance for detecting established AKI even in a heterogeneous disease-oriented population, identification of new biomarkers that predict the development of AKI accurately is urgently required.MethodsA single-center prospective observational cohort study was undertaken to evaluate for the first time the reliability of the newly identified biomarker semaphorin 3A for AKI diagnosis in heterogeneous intensive care unit populations. In addition to five urinary biomarkers of L-type fatty acid-binding protein (L-FABP), neutrophil gelatinase-associated lipocalin (NGAL), IL-18, albumin and N-acetyl-β-d-glucosaminidase (NAG), urinary semaphorin 3A was measured at intensive care unit (ICU) admission.Results and conclusionThree hundred thirty-nine critically ill adult patients were recruited for this study. Among them, 131 patients (39%) were diagnosed with AKI by the RIFLE criteria and 66 patients were diagnosed as AKI at post-ICU admission (later-onset AKI). Eighty-four AKI patients showed worsening severity during 1 week observation (AKI progression). Although L-FABP, NGAL and IL-18 showed significantly higher area under the curve (AUC)-receiver operating characteristic (ROC) values than semaphorin 3A in detecting established AKI, semaphorin 3A was able to detect later-onset AKI and AKI progression with similar AUC-ROC values compared with the other five biomarkers [AUC-ROC (95% CI) for established AKI 0.64 (0.56-0.71), later-onset AKI 0.71 (0.64-0.78), AKI progression 0.71 (0.64-0.77)]. Urinary semaphorin 3A was not increased in non-progressive established AKI, while the other biomarkers were elevated regardless of further progression. Finally, sepsis did not have any impact on semaphorin 3A while the other urinary biomarkers were increased with sepsis. Semaphorin 3A is a new biomarker of AKI which may have a distinct predictive use for AKI progression when compared with other AKI biomarkers.

Dataset Information

Urinary angiotensinogen predicts adverse outcomes among acute kidney injury patients in the intensive care unit.

Introduction

Methods

Results

Conclusions

Publications

Urinary angiotensinogen predicts adverse outcomes among acute kidney injury patients in the intensive care unit.

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