Skip to main content

Main menu

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • ASN Meeting Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
    • Reprint Information
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Reprint Information
    • Subscriptions
    • Feedback
  • ASN Kidney News
  • Other
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
American Society of Nephrology
  • Other
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Advertisement
American Society of Nephrology

Advanced Search

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • ASN Meeting Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
    • Reprint Information
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Reprint Information
    • Subscriptions
    • Feedback
  • ASN Kidney News
  • Visit ASN on Facebook
  • Follow CJASN on Twitter
  • CJASN RSS
  • Community Forum
Original ArticlesAcute Kidney Injury
You have accessRestricted Access

Urinary Biomarkers at the Time of AKI Diagnosis as Predictors of Progression of AKI among Patients with Acute Cardiorenal Syndrome

Chunbo Chen, Xiaobing Yang, Ying Lei, Yan Zha, Huafeng Liu, Changsheng Ma, Jianwei Tian, Pingyan Chen, Tiecheng Yang and Fan Fan Hou
CJASN September 2016, 11 (9) 1536-1544; DOI: https://doi.org/10.2215/CJN.00910116
Chunbo Chen
*Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China;
†Department of Critical Care Medicine, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Cardiovascular Institute, Guangzhou, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiaobing Yang
*Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ying Lei
*Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yan Zha
‡Department of Nephrology, Guizhou Provincial People’s Hospital, Guiyang Medical University, Guiyang, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Huafeng Liu
§Division of Nephrology, Institute of Nephrology, Guangdong Medical College, Zhanjiang, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Changsheng Ma
‖Department of Cardiology, Beijing An Zhen Hospital, Capital Medical University, Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing, China; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jianwei Tian
*Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Pingyan Chen
*Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tiecheng Yang
¶Division of Nephrology, The Futian Hospital, Guangdong Medical College, Shenzhen, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Fan Fan Hou
*Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data Supps
  • Info & Metrics
  • View PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Additional Files
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    Receiver-operating characteristics analyses for predicting AKI progression or AKI progression with death. (A) The area under the receiver operating curve (AUCs) of renal injury biomarkers (urinary angiotensinogen [uAGT], urinary neutrophil gelatinase-associated lipocalin [uNGAL], urinary IL-18 [uIL-18]) and clinical model, at the time of AKI diagnosis, for predicting AKI progression. (B) The AUCs of renal injury biomarkers (uAGT, uNGAL, uIL-18) and clinical model, at the time of AKI diagnosis, for predicting AKI progression with subsequent death. (C) The performance of combination of renal injury biomarkers for predicting AKI progression. The clinical risk model includes age, gender, hypertension, diabetes, preadmission eGFR, N-terminal pro-B-type natriuretic peptide (NT-proBNP), serum albumin, hemoglobin, diuretic dosage before AKI, use of spironolactone before AKI, use of RAS inhibitors before AKI, and change of serum creatinine from baseline at the time of AKI diagnosis.

Tables

  • Figures
  • Additional Files
    • View popup
    Table 1.

    Characteristics in patients with and without AKI progression

    DemographicsAKI progressionP Value
    Yes (n=50)No (n=163)
    Age, y66.8±17.670.6±12.20.09
    Male, n (%)26 (52.0)108 (66.3)0.09
    Hypertension, n (%)24 (48.0)105 (64.4)0.05
    Diabetes, n (%)20 (40.0)55 (33.7)0.49
    Prior CKDa, n (%)22 (44.0)60 (36.8)0.41
    Prior hospitalization for HF, n (%)25 (50.0)88 (54.0)0.63
    Primary diseases of heart failure
     Ischemic heart disease, n (%)28 (56.0)90 (55.2)0.99
     Hypertensive heart disease, n (%)7 (14.0)30 (18.4)0.53
     Rheumatic heart disease, n (%)4 (8.0)11 (6.7)0.76
     Cardiomyopathy, n (%)7 (14.0)21 (12.9)0.81
     Other, n (%)4 (8.0)11 (6.7)0.76
    Preadmission medication
     ACEI/ARB, n (%)15 (30.0)52 (32.0)0.86
     β-blockers, n (%)9 (18.0)40 (24.5)0.44
     Spironolactone, n (%)10 (20.0)44 (27.0)0.36
     Loop diuretics, n (%)14 (28.0)53 (32.5)0.60
    Preadmission (baseline) renal function
     Serum creatinine, mg/dl1.45±0.71.30±0.50.11
     eGFR, ml/min per 1.73m2 b59.1±28.363.4±24.00.29
    Parameters on admission
     LVEF (%)42 (40–63)41 (36–58)0.22
     NYHA (class IV), n (%)20 (40.0)89 (54.6)0.08
     NT-proBNP, pg/ml9000 (3656–24139)6647 (3185–9000)0.02
     Serum creatinine, mg/dl1.6±0.81.5±0.80.41
     Serum albumin, g/dl2.9±0.63.2±0.50.001
     Serum triglyceride, mmol/L1.6±0.81.7±0.70.39
     Serum cholesterol, mmol/L3.8±0.93.8±0.60.99
     Serum sodium, mmol/L138.3±5.0138.0±5.00.71
     Serum potassium, mmol/L4.2±0.84.1±0.60.34
     Hemoglobin, g/dl10.8±2.411.8±2.60.04
    • Continuous variables were expressed as mean±SD or median (25th percentile – 75th percentile, interquartile range). Categorical variables were expressed as a number (%). AKI progression is defined as worsening of AKI stage. HF, heart failure; ACEI, angiotensin converting enzyme inhibitors; ARB, angiotensin II type I receptor blockers; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association; NT-proBNP, N-terminal pro-B-type natriuretic peptide.

    • ↵a Defined as preadmission eGFR<60ml/min per 1.73m2. Preadmission eGFR was calculated by CKD-Epidemiology Collaboration equation according to at least three measurements of serum creatinine over a 6-month period before admission.

    • View popup
    Table 2.

    Characteristics after admission in patients with and without AKI progression

    VariablesAKI progressionP Value
    Yes (n=50)No (n=163)
    Timing of AKI
     AKI on admission, n (%)6 (12.0)22 (13.5)0.99
     Within 4 d after admission, n (%)46 (92.0)135(82.8)0.17
    Use of loop-diureticsa
     Before AKI diagnosis, mg/d46.5±22.140.5±20.60.08
     On the day of AKI diagnosis, mg/d49.0±23.542.1±22.80.06
    Use of spironolactone
     Before AKI diagnosis, n (%)20 (40.0)78 (47.9)0.41
     On the day of AKI diagnosis, n (%)20 (40.0)78 (47.9)0.41
    Use of RAS inhibitors
     Before AKI diagnosis, n (%)19 (38.0)73 (44.8)0.42
     On the day of AKI diagnosis, n (%)19 (38.0)73 (44.8)0.42
    Biomarkers on the day of AKI diagnosis
     SCr, mg/dl2.1±0.851.8±0.70.01
     Change in SCr, mg/dlb0.7±0.50.5±0.40.05
     Change in SCrc, %48.4±27.745.9±23.00.52
     uAGT, μg/g Cr224.5 (108.8–483.8)44.8 (9.3–146.2)<0.001
     pAGT, μg/L27.8±5.726.5±5.50.15
     uNGAL, μg/g Cr311.3 (87.5–1883.8)58.8 (29.8–197.3)<0.001
     pNGAL, ng/ml238.0 (152.9–335.4)179.0 (115.2–258.2)0.001
     uIL-18, ng/g Cr748.4 (68.7–1964.9)52.0 (16.0–215.2)<0.001
     uKIM-1, μg/g Cr4.6 (2.5–8.0)2.6 (1.6–4.9)0.001
     UACR, mg/g Cr292.3 (138.2–964.9)154.0 (49.8–382.0)0.001
    In-hospital outcomes
     Hospital-free daysd0 (0–18)18 (10–20)0.001
     ICU-free daysd13 (0–21)22 (15–24)<0.001
     Acute dialysis, n (%)13 (26.0)0 (0)<0.001
     In-hospital death, n (%)18 (36.0)25 (15.3)0.002
    • Continuous variables were expressed as mean±SD or median (25th percentile – 75th percentile, interquartile range). Categorical variables were expressed as a number (%). SCr, serum creatinine; uAGT, urinary angiotensinogen; pAGT, plasma angiotensinogen; uNGAL, urinary neutrophil gelatinase-associated lipocalin; pNGAL plasma neutrophil gelatinase-associated lipocalin; uIL-18, urinary IL-18; uKIM-1, urinary kidney injury molecule-1; UACR, urinary albumin to creatinine ratio; ICU, Intensive-care unit.

    • ↵a Average daily dose of intravenous furosemide (oral dosage × 0.5, as oral bioavailability is about 50%).

    • ↵b Serum creatinine level on the day of AKI diagnosis minus baseline serum creatinine level.

    • ↵c (SCr level on the day of AKI diagnosis − baseline SCr level)/ baseline SCr level × 100%.

    • ↵d 28 minus the number of hospital or ICU days, with a score of zero assigned to patients who died.

    • View popup
    Table 3.

    Biomarkers for predicting AKI progression: multivariate logistic regression analyses

    BiomarkerCut PointsNAKI Progression (%)Unadjusted OR (95% CI)P ValueAdjusted ORa (95% CI)P Value
    SCr, mg/dl
     Low (T1)0.8–1.47014.31 (referent)0.041 (referent)0.21
     Medium (T2)1.5–2.07223.61.9 (0.8 to 4.3)2.3 (0.8 to 6.6)
     High (T3)>2.07132.42.9 (1.2 to 6.6)2.9 (0.8 to 10.5)
    uAGT, μg/g Cr
     Low (T1)0.04–27.3717.01 (referent)<0.0011 (referent)<0.001
     Medium (T2)27.4–146.47119.73.2 (1.1 to 9.5)3.7 (1.1 to 12.1)
     High (T3)>146.47143.710.2 (3.7 to 28.4)10.8 (3.4 to 34.7)
    uNGAL, μg/g Cr
     Low (T1)0.2–47.4719.91 (referent)<0.0011 (referent)0.01
     Medium (T2)47.5–185.47121.12.4 (0.9 to 6.4)2.0 (0.7 to 5.7)
     High (T3)>185.47139.45.9 (2.4 to 14.8)4.7 (1.7 to 13.4)
    uIL-18, ng/g Cr
     Low (T1)1.2–38.57014.31 (referent)<0.0011 (referent)0.004
     Medium (T2)38.6–224.47211.10.8 (0.3 to 2.0)0.8 (0.3 to 2.3)
     High (T3)>224.47145.14.9 (2.2 to 11.1)3.6 (1.4 to 9.5)
    uKIM-1, μg/g Cr
     Low (T1)0.01–2.27115.51 (referent)0.0021 (referent)0.11
     Medium (T2)2.3–4.67116.91.1 (0.5 to 2.7)0.9 (0.3 to 2.5)
     High (T3)>4.67138.03.3 (1.5 to 7.5)2.1 (0.8 to 5.3)
    UACR, mg/g Cr
     Low (T1)1.0–104.77112.71 (referent)0.021 (referent)0.19
     Medium (T2)104.8–308.57123.92.2 (0.9 to 5.2)1.7 (0.6 to 4.4)
     High (T3)>308.57133.83.5 (1.5 to 8.2)2.5 (0.9 to 6.9)
    pNGAL, ng/ml
     Low (T1)8.8–151.37114.11 (referent)0.041 (referent)0.63
     Medium (T2)151.4–238.07424.32.0 (0.8 to 4.6)1.5 (0.6 to 4.0)
     High (T3)>238.06832.42.9 (1.3 to 6.8)1.2 (0.4 to 3.2)
    • AKI progression is defined as worsening of AKI stage (from stage 1 to either stage 2 or 3 or from stage 2 to 3). Biomarkers are measured at the time of stage 1 or 2 AKI diagnosis. SCr, serum creatinine; T, tertile; uAGT, urinary angiotensinogen; uNGAL, urinary neutrophil gelatinase-associated lipocalin; uIL-18, urinary IL-18; uKIM-1, urinary kidney injury molecule-1; UACR, urinary albumin to creatinine ratio; pNGAL plasma neutrophil gelatinase-associated lipocalin.

    • ↵a Adjusted for age, gender, hypertension, diabetes, preadmission eGFR, NT-proBNP, serum albumin, hemoglobin, diuretic dosage before AKI, use of spironolactone before AKI, use of RAS inhibitors before AKI, and change of serum creatinine from baseline at the time of AKI diagnosis. Site is adjusted as a random effect.

    • View popup
    Table 4.

    NRI and IDI of including biomarkers in the clinical model to predict AKI progression or progression with death

    OutcomeCategory-Free NRI (95% CI)P ValueNRI in Progressors (95% CI)P ValueNRI in Nonprogressors (95% CI)P ValueIDI (95% CI)P Value
    Predicting AKI progression
     Clinical risk factorsareferentreferent
     Clinical risk factors plus uAGT0.76 (0.46–1.06)<0.0010.48 (0.22–0.74)<0.0010.28 (0.13–0.43)<0.0010.14 (0.10–0.18)<0.001
     Clinical risk factors plus uNGAL0.64 (0.32–0.96)<0.0010.28 (0.01–0.56)0.040.36 (0.21–0.51)<0.0010.11 (0.07–0.15)<0.001
     Clinical risk factors plus uIL-180.60 (0.30–0.90)<0.0010.36 (0.10–0.62)0.010.24 (0.08–0.40)0.0020.09 (0.05–0.13)<0.001
     Clinical risk factors plus pNGAL0.23 (−0.09–0.55)0.15−0.08 (-0.36–0.20)0.570.31 (0.17–0.45)<0.0010.04 (0.00–0.08)0.01
     Clinical risk factors plus uKIM-10.17 (−0.15–0.49)0.290.24 (-0.04–0.52)0.08−0.07 (−0.23–0.09)0.390.01 (0.00–0.03)0.30
     Clinical risk factors plus UACR0.03 (−0.29–0.35)0.870.24 (−0.04–0.52)0.09−0.21 (−0.37 to −0.05)0.0060.01 (0.00–0.03)0.36
    Predicting AKI progression  with death
     Clinical risk factorsareferentreferent
     Clinical risk factors plus uAGT0.93 (0.50–1.36)<0.0010.44 (-0.01–0.90)0.060.49 (0.37–0.61)<0.0010.19 (0.09–0.29)<0.001
     Clinical risk factors plus uNGAL0.86 (0.43–1.30)<0.0010.44 (-0.01–0.90)0.060.42 (0.30–0.54)<0.0010.07 (0.01–0.13)0.04
     Clinical risk factors plus uIL-180.88 (0.45–1.31)<0.0010.44 (-0.01–0.90)0.060.44 (0.32–0.56)<0.0010.08 (0.00–0.16)0.03
    • AKI progression is defined as worsening of AKI stage (from stage 1 to either stage 2 or 3 or from stage 2 to 3). NRI, net reclassification improvement; IDI, integrated discrimination improvement.

    • ↵a The clinical risk factors for AKI progression are comprised of age, gender, hypertension, diabetes, preadmission eGFR, NT-proBNP, serum albumin, hemoglobin, diuretic dosage before AKI, use of spironolactone before AKI, use of RAS inhibitors before AKI, and change of serum creatinine from baseline at the time of AKI diagnosis.

Additional Files

  • Figures
  • Tables
  • Supplemental Data

    • Supplemental Data
PreviousNext
Back to top

In this issue

Clinical Journal of the American Society of Nephrology: 11 (9)
Clinical Journal of the American Society of Nephrology
Vol. 11, Issue 9
September 07, 2016
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
View Selected Citations (0)
Print
Download PDF
Sign up for Alerts
Email Article
Thank you for your help in sharing the high-quality science in CJASN.
Enter multiple addresses on separate lines or separate them with commas.
Urinary Biomarkers at the Time of AKI Diagnosis as Predictors of Progression of AKI among Patients with Acute Cardiorenal Syndrome
(Your Name) has sent you a message from American Society of Nephrology
(Your Name) thought you would like to see the American Society of Nephrology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Urinary Biomarkers at the Time of AKI Diagnosis as Predictors of Progression of AKI among Patients with Acute Cardiorenal Syndrome
Chunbo Chen, Xiaobing Yang, Ying Lei, Yan Zha, Huafeng Liu, Changsheng Ma, Jianwei Tian, Pingyan Chen, Tiecheng Yang, Fan Fan Hou
CJASN Sep 2016, 11 (9) 1536-1544; DOI: 10.2215/CJN.00910116

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Urinary Biomarkers at the Time of AKI Diagnosis as Predictors of Progression of AKI among Patients with Acute Cardiorenal Syndrome
Chunbo Chen, Xiaobing Yang, Ying Lei, Yan Zha, Huafeng Liu, Changsheng Ma, Jianwei Tian, Pingyan Chen, Tiecheng Yang, Fan Fan Hou
CJASN Sep 2016, 11 (9) 1536-1544; DOI: 10.2215/CJN.00910116
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Disclosures
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data Supps
  • Info & Metrics
  • View PDF

More in this TOC Section

Original Articles

  • Trends in Discard of Kidneys from Hepatitis C Viremic Donors in the United States
  • Availability, Accessibility, and Quality of Conservative Kidney Management Worldwide
  • Zolpidem Versus Trazodone Initiation and the Risk of Fall-Related Fractures among Individuals Receiving Maintenance Hemodialysis
Show more Original Articles

Acute Kidney Injury

  • A Decision-Making Algorithm for Initiation and Discontinuation of RRT in Severe AKI
  • Association of Preoperative Urinary Uromodulin with AKI after Cardiac Surgery
  • Vancomycin and the Risk of AKI: A Systematic Review and Meta-Analysis
Show more Acute Kidney Injury

Cited By...

  • Urinary Matrix Metalloproteinase-7 Predicts Severe AKI and Poor Outcomes after Cardiac Surgery
  • Urinary Angiotensinogen: A Promising Biomarker of AKI Progression in Acute Decompensated Heart Failure: What Does It Mean?
  • Google Scholar

Similar Articles

Related Articles

  • Urinary Angiotensinogen: A Promising Biomarker of AKI Progression in Acute Decompensated Heart Failure: What Does It Mean?
  • PubMed
  • Google Scholar

Keywords

  • acute kidney injury
  • Biomarkers
  • prediction
  • outcomes
  • adult
  • angiotensinogen
  • Area Under Curve
  • Cardio-Renal Syndrome
  • creatinine
  • Humans
  • Prospective Studies

Articles

  • Current Issue
  • Early Access
  • Subject Collections
  • Article Archive
  • ASN Meeting Abstracts

Information for Authors

  • Submit a Manuscript
  • Trainee of the Year
  • Author Resources
  • ASN Journal Policies
  • Reuse/Reprint Policy

About

  • CJASN
  • ASN
  • ASN Journals
  • ASN Kidney News

Journal Information

  • About CJASN
  • CJASN Email Alerts
  • CJASN Key Impact Information
  • CJASN Podcasts
  • CJASN RSS Feeds
  • Editorial Board

More Information

  • Advertise
  • ASN Podcasts
  • ASN Publications
  • Become an ASN Member
  • Feedback
  • Follow on Twitter
  • Password/Email Address Changes
  • Subscribe

© 2021 American Society of Nephrology

Print ISSN - 1555-9041 Online ISSN - 1555-905X

Powered by HighWire