Derivation and validation of risk scores to predict cerebrovascular mortality among incident peritoneal dialysis patients

Background/Aims: Cerebrovascular disease (CeVD) is one of the leading causes of death in patients initialising peritoneal dialysis (PD). Currently there is no risk score to predict the future risk of CeVD on entry into PD. This study aimed to derive and validate a risk prediction model for CeVD mortality in 2 years after the initialisation of PD. Methods: All patients registered with the Henan Peritoneal Dialysis Registry (HPDR) between 2007 and 2014 were included. Multivariable logistic regression modelling was applied to derive the risk score. All accessible clinical measurements were screened as potential predictors. Internal validation through bootstrapping was applied to test the model performance. Results: The absolute risk of CeVD mortality was 2.9%. Systolic and diastolic blood pressure, total cholesterol, phosphate, and sodium concentrations were the strongest predictors of CeVD mortality in the final risk score. Good model discrimination with C statistics above 0.70 and calibration of agreed observed and predicted risks were identified in the model. Conclusion: The new risk score, developed and validated using clinical measurements that are accessible on entry into PD, could be used clinically to screen for patients at high risk of CeVD mortality. Such patients might benefit from therapies reducing the incidence of CeVD related events