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Review
. 2023 Jun;55(6):1609-1617.
doi: 10.1007/s11255-023-03470-y. Epub 2023 Jan 31.

A nomogram for predicting the 4-year risk of chronic kidney disease among Chinese elderly adults

Lijuan Zhang  1 , Lan Tang  2 , Siyu Chen  1 , Chen Chen  1 , Bin Peng  3
Affiliations
Review

A nomogram for predicting the 4-year risk of chronic kidney disease among Chinese elderly adults

Lijuan Zhang et al. Int Urol Nephrol. 2023 Jun.

Abstract

Background: Chronic kidney disease (CKD) has become a major public health problem across the globe, leading to various complications. This study aimed to construct a nomogram to predict the 4-year risk of CKD among Chinese adults.

Methods: The study was based on the China Health and Retirement Longitudinal Study (CHARLS). A total of 3562 participants with complete information in CHARLS2011 and CHARLS2015 were included, and further divided into the training cohort and the validation cohort by a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to select variables of the nomogram. The nomogram was evaluated by receiver-operating characteristic curve, calibration plots, and decision curve analysis (DCA).

Results: In all, 2494 and 1068 participants were included in the training cohort and the validation cohort, respectively. A total of 413 participants developed CKD in the following 4 years. Five variables selected by multivariate logistic regression were incorporated in the nomogram, consisting of gender, hypertension, the estimated glomerular filtration rate (eGFR), hemoglobin, and Cystatin C. The area under curve was 0.809 and 0.837 in the training cohort and the validation cohort, respectively. The calibration plots showed agreement between the nomogram-predicted probability and the observed probability. DCA indicated that the nomogram had potential clinical use.

Conclusions: A predictive nomogram was established and internally validated in aid of identifying individuals at increased risk of CKD.

Keywords: CHARLS; Chronic kidney disease; Elderly adults; Nomogram.

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