Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0212590
Title: Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease
Authors: Lim, Cynthia C
Chee, Miao Li
Cheng, Ching-Yu 
Kwek, Jia Liang 
Foo, Majorie
Wong, Tien Yin 
Sabanayagam, Charumathi 
Keywords: Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
EYE DISEASES
PREVALENCE
PROGRESSION
ASSOCIATION
METHODOLOGY
VALIDATION
ALBUMIN
PEOPLE
COHORT
Issue Date: 22-Feb-2019
Publisher: PUBLIC LIBRARY SCIENCE
Citation: Lim, Cynthia C, Chee, Miao Li, Cheng, Ching-Yu, Kwek, Jia Liang, Foo, Majorie, Wong, Tien Yin, Sabanayagam, Charumathi (2019-02-22). Simplified end stage renal failure risk prediction model for the low-risk general population with chronic kidney disease. PLOS ONE 14 (2). ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0212590
Abstract: © 2019 Lim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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/1.73m 2 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.
Source Title: PLOS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/169451
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0212590
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