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Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease.

Publication ,  Journal Article
Lim, CC; Chee, ML; Cheng, C-Y; Kwek, JL; Foo, M; Wong, TY; Sabanayagam, C
Published in: PLoS One
2019

BACKGROUND: Chronic kidney disease (CKD) contributes significant morbidity and mortality among Asians; hence interventions should focus on those most at-risk of progression. However, current end stage renal failure (ESRF) risk stratification tools are complex and not validated in multi-ethnic Asians. We hence aimed to develop an ESRF risk prediction model by taking into account ethnic differences within a fairly homogenous socioeconomic setting and using parameters readily accessible to primary care clinicians managing the vast majority of patients with CKD. METHODS: We performed a prospective cohort study of 1970 adults with CKD estimated glomerular filtration rate <60 ml/min/1.73m2 or albuminuria >30 mg/g from the population-based Singapore Epidemiology of Eye Diseases study (n = 10,033). Outcome was incident ESRF, ascertained by linkage to the Singapore Renal Registry until 2015. RESULTS: Mean follow up was 8.5 ± 1.8 years and ESRF occurred in 32 individuals (1.6%). ESRF incidence rates were 2.8, 0.8 and 2.6 per 1000 patient years in Malays, Indians and Chinese respectively. The best ESRF prediction model included age, gender, eGFR and albuminuria (calibration χ2 = 0.45, P = 0.93; C-statistic 0.933, 95% confidence interval (CI) 0.889-0.978, p = 0.01; AIC 356). Addition of ethnicity improved discrimination marginally (C statistic 0.942, 95% CI 0.903-0.981, p = 0.21). Addition of clinical variables such as diabetes and hyperlipidemia did not improve model performance significantly. CONCLUSION: We affirmed the utility of commonly available clinical information (age, gender, eGFR and UACR) in prognosticating ESRF for multi-ethnic Asians with CKD.

Duke Scholars

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Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2019

Volume

14

Issue

2

Start / End Page

e0212590

Location

United States

Related Subject Headings

  • Risk Factors
  • Registries
  • Prospective Studies
  • Predictive Value of Tests
  • Models, Biological
  • Middle Aged
  • Male
  • Kidney Failure, Chronic
  • Humans
  • Glomerular Filtration Rate
 

Citation

APA
Chicago
ICMJE
MLA
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Lim, C. C., Chee, M. L., Cheng, C.-Y., Kwek, J. L., Foo, M., Wong, T. Y., & Sabanayagam, C. (2019). Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease. PLoS One, 14(2), e0212590. https://doi.org/10.1371/journal.pone.0212590
Lim, Cynthia C., Miao Li Chee, Ching-Yu Cheng, Jia Liang Kwek, Majorie Foo, Tien Yin Wong, and Charumathi Sabanayagam. “Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease.PLoS One 14, no. 2 (2019): e0212590. https://doi.org/10.1371/journal.pone.0212590.
Lim CC, Chee ML, Cheng C-Y, Kwek JL, Foo M, Wong TY, et al. Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease. PLoS One. 2019;14(2):e0212590.
Lim, Cynthia C., et al. “Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease.PLoS One, vol. 14, no. 2, 2019, p. e0212590. Pubmed, doi:10.1371/journal.pone.0212590.
Lim CC, Chee ML, Cheng C-Y, Kwek JL, Foo M, Wong TY, Sabanayagam C. Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease. PLoS One. 2019;14(2):e0212590.

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2019

Volume

14

Issue

2

Start / End Page

e0212590

Location

United States

Related Subject Headings

  • Risk Factors
  • Registries
  • Prospective Studies
  • Predictive Value of Tests
  • Models, Biological
  • Middle Aged
  • Male
  • Kidney Failure, Chronic
  • Humans
  • Glomerular Filtration Rate