A Predictive Nomogram for Selective Screening of Chronic Kidney Disease: A Population-Based Study.

OBJECTIVES

Chronic kidney disease (CKD) is associated with disability, low quality of life, and mortality. However, most cases are asymptomatic, often detected incidentally, or only recognized when they have progressed to the later stages with complications. The present study aimed to determine the prevalence of CKD and develop a predictive nomogram for CKD in Vietnamese adults.

METHODS

This cross-sectional, population-based study involved 533 men and 957 women aged 18 years and older who were screened for CKD. The CKD was diagnosed using the albumin-to-creatinine ratio and/or estimated glomerular filtration rate by the CKD-EPI 2009 equation based on serum creatinine, age, gender, and race (these tests included a baseline measurement and a repeat measurement after 3 months) according to the KDIGO 2012 guideline. We used the Bayesian Model Averaging method to identify the optimal model for predicting CKD. A predictive nomogram was also developed to enable risk prediction.

RESULTS

The overall CKD prevalence was 13.1% (95% confidence interval [CI] = 11.6-14.6), with a prevalence of 11.8% (95% CI = 9.1-14.5) in men and 13.8% (95% CI = 11.6-16) in women. The optimal model for predicting CKD included age (odds ratio [OR] per 5-year increase = 1.19; 95% CI = 1.11-1.28), hypertension (OR = 2.08; 95% CI = 1.50-2.89), and diabetes (OR = 1.69; 95% CI = 1.18-2.43). The area under the receiver operating characteristic curve was 0.7, with a 95% CI ranging from 0.65 to 0.73.

CONCLUSIONS

The CKD is relatively common among Vietnamese adults. A simple model-including age, hypertension, and diabetes-is helpful for the selective screening of CKD in Vietnamese individuals.