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Sci Rep. 2017 Oct 24;7(1):13889. doi: 10.1038/s41598-017-14489-4.

Nomogram for Predicting Cardiovascular Mortality in Incident Peritoneal Dialysis Patients: An Observational Study.

Xia X1,2, Zhao C1,2,3, Luo Q1,2, Zhou Q1,2, Lin Z1,2, Guo X4,5, Wang X4,5,6, Lin J1,2, Yang X1,2, Yu X1,2, Huang F7,8.

Author information

1
The First Affiliated Hospital of Sun Yat-sen University, Department of Nephrology, Guangzhou, 510080, People's Republic of China.
2
Ministry of Health and Guangdong Province, Key Laboratory of Nephrology, Guangzhou, 510080, People's Republic of China.
3
Anhui Provincial Hospital Affiliated to Anhui Medical University, Department of Nephrology, Hefei, 230001, People's Republic of China.
4
School of Mathematics & Computational Science, Sun Yat-sen University, Department of Statistical Science, Guangzhou, 510275, People's Republic of China.
5
Sun Yat-Sen University, Southern China Research Center of Statistical Science, Guangzhou, 510275, People's Republic of China.
6
Sun Yat-Sen University, Zhongshan School of Medicine, Guangzhou, 510080, People's Republic of China.
7
The First Affiliated Hospital of Sun Yat-sen University, Department of Nephrology, Guangzhou, 510080, People's Republic of China. hfxyl@163.net.
8
Ministry of Health and Guangdong Province, Key Laboratory of Nephrology, Guangzhou, 510080, People's Republic of China. hfxyl@163.net.

Abstract

Cardiovascular mortality risk is high for peritoneal dialysis (PD) patients but it varies considerably among individuals. There is no clinical tool to predict cardiovascular mortality for PD patients yet. Therefore, we developed a cardiovascular mortality risk nomogram in a PD patient cohort. We derived and internally validated the nomogram in incident adult PD patients randomly assigned to a training (N = 918) or a validation (N = 460) dataset. The nomogram was built using the LASSO Cox regression model. Increasing age, history of cardiovascular disease or diabetes were consistent predictors of cardiovascular mortality. Low hemoglobin and serum albumin, high hypersensitive C-reactive protein and decreasing 24 hours urine output were identified as non-traditional cardiovascular risk predictors. In the validation dataset, the above nomogram performed good discrimination (1 year c-statistic = 0.83; 3 year c-statistic = 0.78) and calibration. This tool can classify patients between those at high risk of cardiovascular mortality (high-risk group) and those of low risk (low-risk group). Cardiovascular mortality was significantly different in the internal validation set of patients for the high-risk group compared to the low-risk group (HR 3.77, 2.14-6.64; p < 0.001). This novel nomogram can accurately predict cardiovascular mortality risk in incident PD patients.

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