Literature DB >> 28185105

Evaluation of the Framingham Heart Study risk factors and risk score for incident chronic kidney disease at 10 years in a Thai general population.

Krittika Saranburut1, Prin Vathesatogkit2, Anchalee Chittamma3, Somlak Vanavanan3, Nisakron Thongmung4, Tuangrat Tangstheanphan5, Piyamitr Sritara2, Chagriya Kitiyakara6.   

Abstract

PURPOSE: Asians have some of the highest rates of end-stage renal disease, but there is limited information on the risk factors for chronic kidney disease (CKD) in the Asian general population. A risk score for incident CKD for the general population has been developed from the US Framingham Heart Study (FHS) Offspring cohort. This score has been validated on Caucasians and African-Americans, but has not been tested on Asians. We aimed to assess the importance of the FHS risk factors and the performance of the FHS risk score in predicting incident CKD at 10 years in a Thai community-based population.
METHODS: This is a prospective study to evaluate the risk factors and the performance of the FHS risk score comprising of age, diabetes, hypertension, proteinuria, and GFR in predicting incident CKD at 10 years in employees (n = 2568) of the Electric Generating Authority of Thailand.
RESULTS: After excluding subjects with CKD at baseline, 10.4% developed incident CKD defined by the MDRD equation and 10.0% by the CKD-EPI equation. Diabetes, hypertension, and baseline GFR were strong predictors of incident CKD, but proteinuria was not. The agreement between the observed rates and the rates predicted by the FHS risk score was not high (MDRD: χ 2 = 30, P < 0.001; CKD-EPI: χ 2 = 256, P < 0.001), and the discrimination of incident CKD was modest (AUROC (95% CI): MDRD, 0.69 (0.66-0.73); CKD-EPI, 0.63 (0.57-0.65).
CONCLUSIONS: Although diabetes, hypertension, and baseline GFR were important risk factors, the FHS risk score might not be sufficiently accurate at estimating incident CKD in an Asian general population.

Entities:  

Keywords:  Asian; Chronic kidney disease; Cohort; EGAT; Framingham; Population; Risk score; Thai

Mesh:

Year:  2017        PMID: 28185105     DOI: 10.1007/s11255-017-1530-1

Source DB:  PubMed          Journal:  Int Urol Nephrol        ISSN: 0301-1623            Impact factor:   2.370


  25 in total

1.  K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification.

Authors: 
Journal:  Am J Kidney Dis       Date:  2002-02       Impact factor: 8.860

2.  Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation.

Authors:  R B D'Agostino; S Grundy; L M Sullivan; P Wilson
Journal:  JAMA       Date:  2001-07-11       Impact factor: 56.272

Review 3.  Predicting initiation and progression of chronic kidney disease: Developing renal risk scores.

Authors:  M W Taal; B M Brenner
Journal:  Kidney Int       Date:  2006-09-13       Impact factor: 10.612

Review 4.  Chronic kidney disease.

Authors:  Andrew S Levey; Josef Coresh
Journal:  Lancet       Date:  2011-08-15       Impact factor: 79.321

Review 5.  Early recognition and prevention of chronic kidney disease.

Authors:  Matthew T James; Brenda R Hemmelgarn; Marcello Tonelli
Journal:  Lancet       Date:  2010-04-10       Impact factor: 79.321

6.  Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.

Authors:  W T Friedewald; R I Levy; D S Fredrickson
Journal:  Clin Chem       Date:  1972-06       Impact factor: 8.327

7.  A risk score for chronic kidney disease in the general population.

Authors:  Conall M O'Seaghdha; Asya Lyass; Joseph M Massaro; James B Meigs; Josef Coresh; Ralph B D'Agostino; Brad C Astor; Caroline S Fox
Journal:  Am J Med       Date:  2012-03       Impact factor: 4.965

8.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1983-09       Impact factor: 11.105

Review 9.  CKD and Infectious Diseases in Asia Pacific: Challenges and Opportunities.

Authors:  Vivekanand Jha; Narayan Prasad
Journal:  Am J Kidney Dis       Date:  2016-03-02       Impact factor: 8.860

10.  A simple algorithm to predict incident kidney disease.

Authors:  Abhijit V Kshirsagar; Heejung Bang; Andrew S Bomback; Suma Vupputuri; David A Shoham; Lisa M Kern; Philip J Klemmer; Madhu Mazumdar; Phyllis A August
Journal:  Arch Intern Med       Date:  2008-12-08
View more
  1 in total

1.  Systematic review of diagnostic and prognostic models of chronic kidney disease in low-income and middle-income countries.

Authors:  Diego J Aparcana-Granda; Edson J Ascencio; Rodrigo M Carrillo Larco
Journal:  BMJ Open       Date:  2022-03-15       Impact factor: 2.692

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.