You are seeing this message because your Web browser does not support basic Web standards. Find out more about why this message is appearing and what you can do to make your experience on this site better.


Advertisement

ABOUT ARCHIVES
Advanced Search

Welcome   | My Account | E-mail Alerts | RSS | Access Rights | Sign In


  Vol. 168 No. 22, Dec 8/22, 2008 TABLE OF CONTENTS
  Online Only
 •  Online First Table of
Contents
  Original Investigation
 •Online Features
 This Article
 •Full text
 •PDF
 • Reply to article
 •Send to a friend
 • Save in My Folder
 •Save to citation manager
 •Permissions
 Citing Articles
 •Citation map
 •Citing articles on HighWire
 •Citing articles on Web of Science (25)
 •Contact me when this article is cited
 Related Content
 •Related article
 •Similar articles in this journal
 Topic Collections
 •Cardiovascular System
 •Renal Diseases
 •Renal Diseases, Other
 •Women's Health
 •Women's Health, Other
 •Cardiovascular Disease/ Myocardial Infarction
 •Endocrine Diseases
 •Diabetes Mellitus
 •Congestive Heart Failure/ Cardiomyopathy
 •Hematology/ Hematologic Malignancies
 •Anemias
 •Hypertension
 •Alert me on articles by topic
 Social Bookmarking
  Add to CiteULike Add to Connotea Add to Delicious Add to Digg Add to Facebook Add to Reddit Add to Technorati Add to Twitter What's this?

A Simple Algorithm to Predict Incident Kidney Disease

Abhijit V. Kshirsagar, MD, MPH; Heejung Bang, PhD; Andrew S. Bomback, MD; Suma Vupputuri, PhD; David A. Shoham, PhD; Lisa M. Kern, MD, MPH; Philip J. Klemmer, MD; Madhu Mazumdar, PhD; Phyllis A. August, MD, MPH

Arch Intern Med. 2008;168(22):2466-2473.

Background  Despite the growing burden of chronic kidney disease (CKD), there are no algorithms (to our knowledge) to quantify the effect of concurrent risk factors on the development of incident disease.

Methods  A combined cohort (N = 14 155) of 2 community-based studies, the Atherosclerosis Risk in Communities Study and the Cardiovascular Health Study, was formed among men and women 45 years or older with an estimated glomerular filtration rate (GFR) exceeding 60 mL/min/1.73 m2 at baseline. The primary outcome was the development of a GFR less than 60 mL/min/1.73 m2 during a follow-up period of up to 9 years. Three prediction algorithms derived from the development data set were evaluated in the validation data set.

Results  The 3 prediction algorithms were continuous and categorical best-fitting models with 10 predictors and a simplified categorical model with 8 predictors. All showed discrimination with area under the receiver operating characteristic curve in a range of 0.69 to 0.70. In the simplified model, age, anemia, female sex, hypertension, diabetes mellitus, peripheral vascular disease, and history of congestive heart failure or cardiovascular disease were associated with the development of a GFR less than 60 mL/min/1.73 m2. A numeric score of at least 3 using the simplified algorithm captured approximately 70% of incident cases (sensitivity) and accurately predicted a 17% risk of developing CKD (positive predictive value).

Conclusions  An algorithm containing commonly understood variables helps to stratify middle-aged and older individuals at high risk for future CKD. The model can be used to guide population-level prevention efforts and to initiate discussions between practitioners and patients about risk for kidney disease.


Author Affiliations: Division of Nephrology and Hypertension, Department of Medicine, School of Medicine (Drs Kshirsagar, Bomback, and Klemmer), Department of Epidemiology, School of Public Health (Drs Vupputuri and Shoham), and University of North Carolina Kidney Center (Drs Kshirsagar, Bomback, Vupputuri, Shoham, and Klemmer), University of North Carolina at Chapel Hill; and Divisions of Biostatistics and Epidemiology (Drs Bang and Mazumdar) and Health Outcomes and Effectiveness Research (Drs Kern and August), Department of Public Health, and Division of Nephrology and Hypertension, Department of Medicine (Dr August), Weill Medical College of Cornell University, New York, New York. Dr Vupputuri is now with the Center for Health Research, Kaiser Permanente, Atlanta, Georgia. Dr Shoham is now with the Department of Preventive Medicine and Epidemiology, Loyola University, Chicago, Illinois.



Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Delicious Delicious   Add to Digg Digg   Add to Facebook Facebook   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter     What's this?

RELATED ARTICLE

In This Issue of Archives of Internal Medicine
Arch Intern Med. 2008;168(22):2400.
FULL TEXT  


THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES

Association of apolipoprotein A1 and B with kidney function and chronic kidney disease in two multiethnic population samples
Goek et al.
Nephrol Dial Transplant 2012;0:gfr795v1-gfr795.
ABSTRACT | FULL TEXT  

Urinary albumin excretion within the normal range is an independent risk for near-term development of kidney disease in HIV-infected patients
Ando et al.
Nephrol Dial Transplant 2011;26:3923-3929.
ABSTRACT | FULL TEXT  

Relationship between Blood Pressure and Incident Chronic Kidney Disease in Hypertensive Patients
Hanratty et al.
CJASN 2011;6:2605-2611.
ABSTRACT | FULL TEXT  

Development and Validation of a General Population Renal Risk Score
Halbesma et al.
CJASN 2011;6:1731-1738.
ABSTRACT | FULL TEXT  

Predicting Renal Risk in the General Population: Do We Have the Right Formula?
Taal
CJASN 2011;6:1523-1525.
FULL TEXT  

A Multi-Marker Approach to Predict Incident CKD and Microalbuminuria
Fox et al.
J. Am. Soc. Nephrol. 2010;21:2143-2149.
ABSTRACT | FULL TEXT  

Incident chronic kidney disease and the rate of kidney function decline in individuals with hypertension
Hanratty et al.
Nephrol Dial Transplant 2010;25:801-807.
ABSTRACT | FULL TEXT  

Development and Validation of a Patient Self-assessment Score for Diabetes Risk
Bang et al.
ANN INTERN MED 2009;151:775-783.
ABSTRACT | FULL TEXT  

Screening for kidney disease in vascular patients: SCreening for Occult REnal Disease (SCORED) experience
Bang et al.
Nephrol Dial Transplant 2009;24:2452-2457.
ABSTRACT | FULL TEXT  





HOME | CURRENT ISSUE | PAST ISSUES | TOPIC COLLECTIONS | CME | PHYSICIAN JOBS | SUBMIT | SUBSCRIBE | HELP
CONDITIONS OF USE | PRIVACY POLICY | CONTACT US | SITE MAP
 
© 2008 American Medical Association. All Rights Reserved.